Image enhancement with MatLab algorithms

Nowadays, a lot of applications use digital images. For example in face recognition to detect and tag persons in photograph, for security control, and a lot of applications that can be found in smart cities, as speed control in roads or highways and cameras in traffic lights to detect drivers ignoring red light. Also in medicine digital images are used, such as x-ray, scanners, etc. These applications depend on the quality of the image obtained. A good camera is expensive, and the image obtained depends also on external factor as light. To make these applications work properly, image enhancement is as important as, for example, a good face detection algorithm. Image enhancement also can be used in normal photograph, for pictures done in bad light conditions, or just to improve the contrast of an image. There are some applications for smartphones that allow users apply filters or change the bright, colour or contrast on the pictures. This project compares four different techniques to use in image enhancement. After applying one of these techniques to an image, it will use better the whole available dynamic range. Some of the algorithms are designed for grey scale images and others for colour images. It is used Matlab software to develop and present the final results. These algorithms are Successive Means Quantization Transform (SMQT), Histogram Equalization, using Matlab function and own implemented function, and V transform. Finally, as conclusions, we can prove that Histogram equalization algorithm is the simplest of all, it has a wide variability of grey levels and it is not suitable for colour images. V transform algorithm is a good option for colour images. The algorithm is linear and requires low computational power. SMQT algorithm is non-linear, insensitive to gain and bias and it can extract structure of the data. RESUMEN. Hoy en día incontable número de aplicaciones usan imágenes digitales. Por ejemplo, para el control de la seguridad se usa el reconocimiento de rostros para detectar y etiquetar personas en fotografías o vídeos, para distintos usos de las ciudades inteligentes, como control de velocidad en carreteras o autopistas, cámaras en los semáforos para detectar a conductores haciendo caso omiso de un semáforo en rojo, etc. También en la medicina se utilizan imágenes digitales, como por ejemplo, rayos X, escáneres, etc. Todas estas aplicaciones dependen de la calidad de la imagen obtenida. Una buena cámara es cara, y la imagen obtenida depende también de factores externos como la luz. Para hacer que estas aplicaciones funciones correctamente, el tratamiento de imagen es tan importante como, por ejemplo, un buen algoritmo de detección de rostros. La mejora de la imagen también se puede utilizar en la fotografía no profesional o de consumo, para las fotos realizadas en malas condiciones de luz, o simplemente para mejorar el contraste de una imagen. Existen aplicaciones para teléfonos móviles que permiten a los usuarios aplicar filtros y cambiar el brillo, el color o el contraste en las imágenes. Este proyecto compara cuatro técnicas diferentes para utilizar el tratamiento de imagen. Se utiliza la herramienta de software matemático Matlab para desarrollar y presentar los resultados finales. Estos algoritmos son Successive Means Quantization Transform (SMQT), Ecualización del histograma, usando la propia función de Matlab y una nueva función que se desarrolla en este proyecto y, por último, una función de transformada V. Finalmente, como conclusión, podemos comprobar que el algoritmo de Ecualización del histograma es el más simple de todos, tiene una amplia variabilidad de niveles de gris y no es adecuado para imágenes en color. El algoritmo de transformada V es una buena opción para imágenes en color, es lineal y requiere baja potencia de cálculo. El algoritmo SMQT no es lineal, insensible a la ganancia y polarización y, gracias a él, se puede extraer la estructura de los datos.

Parallel Computer Vision Algorithms for Graphics Processing Units

La evolución de los teléfonos móviles inteligentes, dotados de cámaras digitales, está provocando una creciente demanda de aplicaciones cada vez más complejas que necesitan algoritmos de visión artificial en tiempo real; puesto que el tamaño de las señales de vídeo no hace sino aumentar y en cambio el rendimiento de los procesadores de un solo núcleo se ha estancado, los nuevos algoritmos que se diseñen para visión artificial han de ser paralelos para poder ejecutarse en múltiples procesadores y ser computacionalmente escalables. Una de las clases de procesadores más interesantes en la actualidad se encuentra en las tarjetas gráficas (GPU), que son dispositivos que ofrecen un alto grado de paralelismo, un excelente rendimiento numérico y una creciente versatilidad, lo que los hace interesantes para llevar a cabo computación científica. En esta tesis se exploran dos aplicaciones de visión artificial que revisten una gran complejidad computacional y no pueden ser ejecutadas en tiempo real empleando procesadores tradicionales. En cambio, como se demuestra en esta tesis, la paralelización de las distintas subtareas y su implementación sobre una GPU arrojan los resultados deseados de ejecución con tasas de refresco interactivas. Asimismo, se propone una técnica para la evaluación rápida de funciones de complejidad arbitraria especialmente indicada para su uso en una GPU. En primer lugar se estudia la aplicación de técnicas de síntesis de imágenes virtuales a partir de únicamente dos cámaras lejanas y no paralelas—en contraste con la configuración habitual en TV 3D de cámaras cercanas y paralelas—con información de color y profundidad. Empleando filtros de mediana modificados para la elaboración de un mapa de profundidad virtual y proyecciones inversas, se comprueba que estas técnicas son adecuadas para una libre elección del punto de vista. Además, se demuestra que la codificación de la información de profundidad con respecto a un sistema de referencia global es sumamente perjudicial y debería ser evitada. Por otro lado se propone un sistema de detección de objetos móviles basado en técnicas de estimación de densidad con funciones locales. Este tipo de técnicas es muy adecuada para el modelado de escenas complejas con fondos multimodales, pero ha recibido poco uso debido a su gran complejidad computacional. El sistema propuesto, implementado en tiempo real sobre una GPU, incluye propuestas para la estimación dinámica de los anchos de banda de las funciones locales, actualización selectiva del modelo de fondo, actualización de la posición de las muestras de referencia del modelo de primer plano empleando un filtro de partículas multirregión y selección automática de regiones de interés para reducir el coste computacional. Los resultados, evaluados sobre diversas bases de datos y comparados con otros algoritmos del estado del arte, demuestran la gran versatilidad y calidad de la propuesta. Finalmente se propone un método para la aproximación de funciones arbitrarias empleando funciones continuas lineales a tramos, especialmente indicada para su implementación en una GPU mediante el uso de las unidades de filtraje de texturas, normalmente no utilizadas para cómputo numérico. La propuesta incluye un riguroso análisis matemático del error cometido en la aproximación en función del número de muestras empleadas, así como un método para la obtención de una partición cuasióptima del dominio de la función para minimizar el error. ABSTRACT The evolution of smartphones, all equipped with digital cameras, is driving a growing demand for ever more complex applications that need to rely on real-time computer vision algorithms. However, video signals are only increasing in size, whereas the performance of single-core processors has somewhat stagnated in the past few years. Consequently, new computer vision algorithms will need to be parallel to run on multiple processors and be computationally scalable. One of the most promising classes of processors nowadays can be found in graphics processing units (GPU). These are devices offering a high parallelism degree, excellent numerical performance and increasing versatility, which makes them interesting to run scientific computations. In this thesis, we explore two computer vision applications with a high computational complexity that precludes them from running in real time on traditional uniprocessors. However, we show that by parallelizing subtasks and implementing them on a GPU, both applications attain their goals of running at interactive frame rates. In addition, we propose a technique for fast evaluation of arbitrarily complex functions, specially designed for GPU implementation. First, we explore the application of depth-image–based rendering techniques to the unusual configuration of two convergent, wide baseline cameras, in contrast to the usual configuration used in 3D TV, which are narrow baseline, parallel cameras. By using a backward mapping approach with a depth inpainting scheme based on median filters, we show that these techniques are adequate for free viewpoint video applications. In addition, we show that referring depth information to a global reference system is ill-advised and should be avoided. Then, we propose a background subtraction system based on kernel density estimation techniques. These techniques are very adequate for modelling complex scenes featuring multimodal backgrounds, but have not been so popular due to their huge computational and memory complexity. The proposed system, implemented in real time on a GPU, features novel proposals for dynamic kernel bandwidth estimation for the background model, selective update of the background model, update of the position of reference samples of the foreground model using a multi-region particle filter, and automatic selection of regions of interest to reduce computational cost. The results, evaluated on several databases and compared to other state-of-the-art algorithms, demonstrate the high quality and versatility of our proposal. Finally, we propose a general method for the approximation of arbitrarily complex functions using continuous piecewise linear functions, specially formulated for GPU implementation by leveraging their texture filtering units, normally unused for numerical computation. Our proposal features a rigorous mathematical analysis of the approximation error in function of the number of samples, as well as a method to obtain a suboptimal partition of the domain of the function to minimize approximation error.

Vibrio cholerae O1 El Tor: Identification of a gene cluster required for the rugose colony type, exopolysaccharide production, chlorine resistance, and biofilm formation

The rugose colony variant of Vibrio cholerae O1, biotype El Tor, is shown to produce an exopolysaccharide, EPSETr, that confers chlorine resistance and biofilm-forming capacity. EPSETr production requires a chromosomal locus, vps, that contains sequences homologous to carbohydrate biosynthesis genes of other bacterial species. Mutations within this locus yield chlorine-sensitive, smooth colony variants that are biofilm deficient. The biofilm-forming properties of EPSETr may enable the survival of V. cholerae O1 within environmental aquatic habitats between outbreaks of human disease.

Expression of the peroxisome proliferator-activated receptor γ (PPARγ) in human atherosclerosis and regulation in macrophages by colony stimulating factors and oxidized low density lipoprotein

The peroxisome proliferator-activated receptor γ (PPARγ) is a ligand-dependent transcription factor that has been demonstrated to regulate fat cell development and glucose homeostasis. PPARγ is also expressed in a subset of macrophages and negatively regulates the expression of several proinflammatory genes in response to natural and synthetic ligands. We here demonstrate that PPARγ is expressed in macrophage foam cells of human atherosclerotic lesions, in a pattern that is highly correlated with that of oxidation-specific epitopes. Oxidized low density lipoprotein (oxLDL) and macrophage colony-stimulating factor, which are known to be present in atherosclerotic lesions, stimulated PPARγ expression in primary macrophages and monocytic cell lines. PPARγ mRNA expression was also induced in primary macrophages and THP-1 monocytic leukemia cells by the phorbol ester 12-O-tetradecanoylphorbol 13-acetate (TPA). Inhibition of protein kinase C blocked the induction of PPARγ expression by TPA, but not by oxLDL, suggesting that more than one signaling pathway regulates PPARγ expression in macrophages. TPA induced the expression of PPARγ in RAW 264.7 macrophages by increasing transcription from the PPARγ1 and PPARγ3 promoters. In concert, these observations provide insights into the regulation of PPARγ expression in activated macrophages and raise the possibility that PPARγ ligands may influence the progression of atherosclerosis.

Odor space and olfactory processing: Collective algorithms and neural implementation

Several basic olfactory tasks must be solved by highly olfactory animals, including background suppression, multiple object separation, mixture separation, and source identification. The large number N of classes of olfactory receptor cells—hundreds or thousands—permits the use of computational strategies and algorithms that would not be effective in a stimulus space of low dimension. A model of the patterns of olfactory receptor responses, based on the broad distribution of olfactory thresholds, is constructed. Representing one odor from the viewpoint of another then allows a common description of the most important basic problems and shows how to solve them when N is large. One possible biological implementation of these algorithms uses action potential timing and adaptation as the “hardware” features that are responsible for effective neural computation.

Autocrine production and action of IL-3 and granulocyte colony-stimulating factor in chronic myeloid leukemia

Primitive subsets of leukemic cells isolated by using fluorescence-activated cell sorting from patients with newly diagnosed Ph+/BCR–ABL+ chronic myeloid leukemia display an abnormal ability to proliferate in vitro in the absence of added growth factors. We now show from analyses of growth-factor gene expression, protein production, and antibody inhibition studies that this deregulated growth can be explained, at least in part, by a novel differentiation-controlled autocrine mechanism. This mechanism involves the consistent and selective activation of IL-3 and granulocyte colony-stimulating factor (G-CSF) production and a stimulation of STAT5 phosphorylation in CD34+ leukemic cells. When these cells differentiate into CD34− cells in vivo, IL-3 and G-CSF production declines, and the cells concomitantly lose their capacity for autonomous growth in vitro despite their continued expression of BCR–ABL. Based on previous studies of normal cells, excessive exposure of the most primitive chronic myeloid leukemia cells to IL-3 and G-CSF through an autocrine mechanism could explain their paradoxically decreased self-renewal in vitro and slow accumulation in vivo, in spite of an increased cycling activity and selective expansion of later compartments.

Dimensionality Reduction Through Sub-Space Mapping for Nearest Neighbour Algorithms

Postprint

Vaccination with irradiated autologous melanoma cells engineered to secrete human granulocyte–macrophage colony-stimulating factor generates potent antitumor immunity in patients with metastatic melanoma

We conducted a Phase I clinical trial investigating the biologic activity of vaccination with irradiated autologous melanoma cells engineered to secrete human granulocyte–macrophage colony-stimulating factor in patients with metastatic melanoma. Immunization sites were intensely infiltrated with T lymphocytes, dendritic cells, macrophages, and eosinophils in all 21 evaluable patients. Although metastatic lesions resected before vaccination were minimally infiltrated with cells of the immune system in all patients, metastatic lesions resected after vaccination were densely infiltrated with T lymphocytes and plasma cells and showed extensive tumor destruction (at least 80%), fibrosis, and edema in 11 of 16 patients examined. Antimelanoma cytotoxic T cell and antibody responses were associated with tumor destruction. These results demonstrate that vaccination with irradiated autologous melanoma cells engineered to secrete granulocyte–macrophage colony-stimulating factor stimulates potent antitumor immunity in humans with metastatic melanoma.

The effect of overexpression of the protein tyrosine phosphatase PTPMEG on cell growth and on colony formation in soft agar in COS-7 cells

We established stable COS-7 cell lines overexpressing recombinant PTPMEG and an inactive mutant form in which the active site cysteine is mutated to serine (PTPMEGCS). We found that both endogenous and recombinant enzyme were primarily located in the membrane and cytoskeletal fractions of COS-7 cells. Endogenous PTPMEG accounts for only 1/3000th of the total tyrosine phosphatase activity in COS-7 cells and transfected cells expressed 2- to 7-fold higher levels of the enzyme. These levels of overexpression did not result in detectable changes in either total tyrosine phosphatase activity or the state of protein tyrosine phosphorylation as determined by immunoblotting of cell homogenates with anti-phosphotyrosine antibodies. Despite the low levels of activity for PTPMEG, we found that overexpressing cells grew slower and reached confluence at a lower density than vector transfected cells. Surprisingly, PTPMEGCS-transfected cells also reach confluence at a lower density than vector-transfected cells, although they grow to higher density than PTPMEG-transfected cells. Both constructs inhibited the ability of COS-7 cells to form colonies in soft agar, with the native PTPMEG having a greater effect (30-fold) than PTPMEGCS (10-fold). These results indicate that in COS-7 cells both PTPMEG and PTPMEGCS inhibit cell proliferation, reduce the saturation density, and block the ability of these cells to grow without adhering to a solid matrix.

Correction of murine galactosialidosis by bone marrow-derived macrophages overexpressing human protective protein/cathepsin A under control of the colony-stimulating factor-1 receptor promoter

Galactosialidosis (GS) is a human neurodegenerative disease caused by a deficiency of lysosomal protective protein/cathepsin A (PPCA). The GS mouse model resembles the severe human condition, resulting in nephropathy, ataxia, and premature death. To rescue the disease phenotype, GS mice were transplanted with bone marrow from transgenic mice overexpressing human PPCA specifically in monocytes/macrophages under the control of the colony stimulating factor-1 receptor promoter. Transgenic macrophages infiltrated and resided in all organs and expressed PPCA at high levels. Correction occurred in hematopoietic tissues and nonhematopoietic organs, including the central nervous system. PPCA-expressing perivascular and leptomeningeal macrophages were detected throughout the brain of recipient mice, although some neuronal cells, such as Purkinje cells, continued to show storage and died. GS mice crossed into the transgenic background reflected the outcome of bone marrow-transplanted mice, but the course of neuronal degeneration was delayed in this model. These studies present definite evidence that macrophages alone can provide a source of corrective enzyme for visceral organs and may be beneficial for neuronal correction if expression levels are sufficient.

Amyloid-β peptide–Receptor for Advanced Glycation Endproduct interaction elicits neuronal expression of macrophage-colony stimulating factor: A proinflammatory pathway in Alzheimer disease

In Alzheimer disease (AD), neurons are thought to be subjected to the deleterious cytotoxic effects of activated microglia. We demonstrate that binding of amyloid-beta peptide (Aβ) to neuronal Receptor for Advanced Glycation Endproduct (RAGE), a cell surface receptor for Aβ, induces macrophage-colony stimulating factor (M-CSF) by an oxidant sensitive, nuclear factor κB-dependent pathway. AD brain shows increased neuronal expression of M-CSF in proximity to Aβ deposits, and in cerebrospinal fluid from AD patients there was ≈5-fold increased M-CSF antigen (P < 0.01), compared with age-matched controls. M-CSF released by Aβ-stimulated neurons interacts with its cognate receptor, c-fms, on microglia, thereby triggering chemotaxis, cell proliferation, increased expression of the macrophage scavenger receptor and apolipoprotein E, and enhanced survival of microglia exposed to Aβ, consistent with pathologic findings in AD. These data delineate an inflammatory pathway triggered by engagement of Aβ on neuronal RAGE. We suggest that M-CSF, thus generated, contributes to the pathogenesis of AD, and that M-CSF in cerebrospinal fluid might provide a means for monitoring neuronal perturbation at an early stage in AD.

The human granulocyte-macrophage colony- stimulating factor gene is autonomously regulated in vivo by an inducible tissue-specific enhancer

The granulocyte-macrophage colony-stimulating factor (GM-CSF) gene is part of a cytokine gene cluster and is directly linked to a conserved upstream inducible enhancer. Here we examined the in vitro and in vivo functions of the human GM-CSF enhancer and found that it was required for the correctly regulated expression of the GM-CSF gene. An inducible DNase I-hypersensitive site appeared within the enhancer in cell types such as T cells, myeloid cells, and endothelial cells that express GM-CSF, but not in nonexpressing cells. In a panel of transfected cells the human GM-CSF enhancer was activated in a tissue-specific manner in parallel with the endogenous gene. The in vivo function of the enhancer was examined in a transgenic mouse model that also addressed the issue of whether the GM-CSF locus was correctly regulated in isolation from other segments of the cytokine gene cluster. After correction for copy number the mean level of human GM-CSF expression in splenocytes from 11 lines of transgenic mice containing a 10.5-kb human GM-CSF transgene was indistinguishable from mouse GM-CSF expression (99% ± 56% SD). In contrast, a 9.8-kb transgene lacking just the enhancer had a significantly reduced (P = 0.004) and more variable level of activity (29% ± 89% SD). From these studies we conclude that the GM-CSF enhancer is required for the correct copy number-dependent expression of the human GM-CSF gene and that the GM-CSF gene is regulated independently from DNA elements associated with the closely linked IL-3 gene or other members of the cytokine gene cluster.

T cell functions in granulocyte/macrophage colony-stimulating factor deficient mice

Immunological functions were analyzed in mice lacking granulocyte/macrophage colony-stimulating factor (GM-CSF). The response of splenic T cells to allo-antigens, anti-mouse CD3 mAb, interleukin 2 (IL-2), or concanavalin A was comparable in GM-CSF +/+ and GM-CSF −/− mice. To investigate the responses of CD8+ and CD4+ T cells against exogenous antigens, mice were immunized with ovalbumin peptide or with keyhole limpet hemocyanin (KLH). Cytotoxic CD8+ T cells with specificity for ovalbumin peptide could not be induced in GM-CSF −/− mice. After immunization with KLH, there was a delay in IgG generation, particularly IgG2a, in GM-CSF −/− mice. Purified CD4+ T cells from GM-CSF −/− mice immunized with KLH showed impaired proliferative responses and produced low amounts of interferon-γ (IFN-γ) and IL-4 when KLH-pulsed B cells or spleen cells were used as antigen presenting cells (APC). When enriched dendritic cells (DC) were used as APC, CD4+ T cells from GM-CSF −/− mice proliferated as well as those from GM-CSF +/+ mice and produced high amounts of IFN-γ and IL-4. To analyze the rescue effect of DC on CD4+ T cells, supernatants from (i) CD4+ T cells cultured with KLH-pulsed DC or (ii) DC cultured with recombinant GM-CSF were transferred to cultures of CD4+ T cells and KLH-pulsed spleen cells from GM-CSF −/− mice. Supernatants from both DC sources contained a factor or factors that restored proliferative responses and IFN-γ production of CD4+ T cells from GM-CSF −/− mice.

Two Distinct Signaling Pathways Downstream of Janus Kinase 2 Play Redundant Roles for Antiapoptotic Activity of Granulocyte-Macrophage Colony-stimulating Factor

Human granulocyte-macrophage colony-stimulating factor (hGM-CSF) induces proliferation and sustains the viability of the mouse interleukin-3-dependent cell line BA/F3 expressing the hGM-CSF receptor. Analysis of the antiapoptosis activity of GM-CSF receptor βc mutants showed that box1 but not the C-terminal region containing tyrosine residues is essential for GM-CSF-dependent antiapoptotic activity. Because βc mutants, which activate Janus kinase 2 but neither signal transducer and activator of transcription 5 nor the MAPK cascade sustain antiapoptosis activity, involvement of Janus kinase 2, excluding the above molecules, in antiapoptosis activity seems likely. GM-CSF activates phosphoinositide-3-OH kinase as well as Akt, and activation of both was suppressed by addition of wortmannin. Interestingly, wortmannin did not affect GM-CSF-dependent antiapoptosis, thus indicating that the phosphoinositide-3-OH kinase pathway is not essential for cell surivival. Analysis using the tyrosine kinase inhibitor genistein and a MAPK/extracellular signal-regulated kinase (ERK) kinase 1 inhibitor, PD98059, indicates that activation of either the genistein-sensitive signaling pathway or the PD98059-sensitive signaling pathway from βc may be sufficient to suppress apoptosis. Wild-type and a βc mutant lacking tyrosine residues can induce expression of c-myc and bcl-xL genes; however, drug sensitivities for activation of these genes differ from those for antiapoptosis activity of GM-CSF, which means that these gene products may be involved yet are inadequate to promote cell survival.