Avaliação de técnicas de classificação digital de imagens landsat em diferentes padrões de cobertura da terra em Rondônia

Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.

Image quality in diagnostic radiology

This chapter provides a theoretical background about image quality in diagnostic radiology. Digital image representation and also image quality evaluation methods are here discussed. An overview of methods for quality evaluation of diagnostic imaging procedures is provided. Digital image representation and primary physical image quality parameters are also discussed, including objective image quality measurements and observer performance methods.

Image upsampling algorithms applied on Nuclear Medicine: comparision of hqnx and nxSaI algorithms families with two interpolation algorithms - nearest neighbour and bicubic interpolation

Introduction: Image resizing is a normal feature incorporated into the Nuclear Medicine digital imaging. Upsampling is done by manufacturers to adequately fit more the acquired images on the display screen and it is applied when there is a need to increase - or decrease - the total number of pixels. This paper pretends to compare the “hqnx” and the “nxSaI” magnification algorithms with two interpolation algorithms – “nearest neighbor” and “bicubic interpolation” – in the image upsampling operations. Material and Methods: Three distinct Nuclear Medicine images were enlarged 2 and 4 times with the different digital image resizing algorithms (nearest neighbor, bicubic interpolation nxSaI and hqnx). To evaluate the pixel’s changes between the different output images, 3D whole image plot profiles and surface plots were used as an addition to the visual approach in the 4x upsampled images. Results: In the 2x enlarged images the visual differences were not so noteworthy. Although, it was clearly noticed that bicubic interpolation presented the best results. In the 4x enlarged images the differences were significant, with the bicubic interpolated images presenting the best results. Hqnx resized images presented better quality than 4xSaI and nearest neighbor interpolated images, however, its intense “halo effect” affects greatly the definition and boundaries of the image contents. Conclusion: The hqnx and the nxSaI algorithms were designed for images with clear edges and so its use in Nuclear Medicine images is obviously inadequate. Bicubic interpolation seems, from the algorithms studied, the most suitable and its each day wider applications seem to show it, being assumed as a multi-image type efficient algorithm.

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

Automating the testing process of image processing algorithms

As digital imaging processing techniques become increasingly used in a broad range of consumer applications, the critical need to evaluate algorithm performance has become recognised by developers as an area of vital importance. With digital image processing algorithms now playing a greater role in security and protection applications, it is of crucial importance that we are able to empirically study their performance. Apart from the field of biometrics little emphasis has been put on algorithm performance evaluation until now and where evaluation has taken place, it has been carried out in a somewhat cumbersome and unsystematic fashion, without any standardised approach. This paper presents a comprehensive testing methodology and framework aimed towards automating the evaluation of image processing algorithms. Ultimately, the test framework aims to shorten the algorithm development life cycle by helping to identify algorithm performance problems quickly and more efficiently.

Sample size for measurement of root traits on common bean by image analysis

Evaluation of root traits may be facilitated if they are assessed on samples of the root system. The objective of this work was to determine the sample size of the root system in order to estimate root traits of common bean (Phaseolus vulgaris L.) cultivars by digital image analysis. One plant was grown per pot and harvested at pod setting, with 64 and 16 pots corresponding to two and four cultivars in the first and second experiments, respectively. Root samples were scanned up to the completeness of the root system and the root area and length were estimated. Scanning a root sample demanded 21 minutes, and scanning the entire root system demanded 4 hours and 53 minutes. In the first experiment, root area and length estimated with two samples showed, respectively, a correlation of 0.977 and 0.860, with these traits measured in the entire root. In the second experiment, the correlation was 0.889 and 0.915. The increase in the correlation with more than two samples was negligible. The two samples corresponded to 13.4% and 16.9% of total root mass (excluding taproot and nodules) in the first and second experiments. Taproot stands for a high proportion of root mass and must be deducted on root trait estimations. Samples with nearly 15% of total root mass produce reliable root trait estimates.

Hardcopy quality parameters to ensure structures detection at digital mammography

Objective To develop procedures to ensure consistency of printing quality of digital images, by means of hardcopy quantitative analysis based on a standard image. Materials and Methods Characteristics of mammography DI-ML and general purpose DI-HL films were studied through the QC-Test utilizing different processing techniques in a FujiFilm®-DryPix4000 printer. A software was developed for sensitometric evaluation, generating a digital image including a gray scale and a bar pattern to evaluate contrast and spatial resolution. Results Mammography films showed maximum optical density of 4.11 and general purpose films, 3.22. The digital image was developed with a 33-step wedge scale and a high-contrast bar pattern (1 to 30 lp/cm) for spatial resolution evaluation. Conclusion Mammographic films presented higher values for maximum optical density and contrast resolution as compared with general purpose films. The utilized digital processing technique could only change the image pixels matrix values and did not affect the printing standard. The proposed digital image standard allows greater control of the relationship between pixels values and optical density obtained in the analysis of films quality and printing systems.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

OBJECTIVE: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. METHODS: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. RESULTS: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). CONCLUSION: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. ADVANCES IN KNOWLEDGE: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

Análise digital de imagem e estereologia da angiogênese em adenomas e no adenocarcinoma colorretal invasivo de submucosa

A angiogênese é essencial no desenvolvimento neoplásico, associando-se às metástases à distância e recorrência em diversas neoplasias malignas. Em carcinomas colorretais, os parâmetros da análise digital de imagem e estereologia da angiogênese foram pouco estudados. Objetivo: avaliar parâmetros tridimensionais e a quantificação microvascular bidimensional nas diferentes apresentações morfológicas dos adenomas colorretais e no adenocarcinoma colorretal restrito à submucosa, a fim de determinar o papel da angiogênese nas diferentes etapas da seqüência adenoma-carcinoma e sua relação com as diferentes apresentações das lesões precursoras do carcinoma colorretal. Material e métodos: foi realizado estudo histórico de delineamento transversal, incluindo 115 lesões neoplásicas colorretais, ressecadas endoscópica ou cirurgicamente no período de 1997 a 2001, obtidas de pacientes do Hospital de Clínicas de Porto Alegre e da Fundação Universitária de Gastroenterologia (FUGAST). Para análise da angiogênese foram utilizadas as técnicas de imuno-histoquímica, análise digital de imagem, quantificação microvascular e estereologia. Os resultados foram apresentados como mediana e intervalos interquartis. Resultados: a quantificação microvascular foi progressivamente mais elevada nas lesões polipóides com displasia de alto grau comparadas às de baixo grau. Quanto maior o grau de atipia observado, maior foi o número de microvasos (regressão linear, P < 0,05). O volume e extensão microvascular foram diferentes entre as fases evolutivas da neoplasia colorretal, resultando em aumento no volume 728 (416 - 1408) versus 178 (93 - 601) e extensão microvascular 242,4 (131,1 - 936,8) vs 24,0 (6,5 - 142,2) (P < 0,001) nas lesões polipóides com displasia de alto grau comparadas às de baixo grau, respectivamente. A quantificação microvascular foi progressivamente mais elevada, acompanhando a progressão neoplásica polipóide: displasia de baixo grau 41,8 (15,8 - 71,9), displasia de alto grau 60,0 (23,0 - 95,6) e carcinoma de submucosa 76,0 (37,5 - 132,6) (P < 0,001). Concomitante, o volume 956 (436 - 2188) vs 178 (93 - 601) e a extensão microvascular 534,6 (146,7 - 1262) vs 24,0 (6,5 - 142,2) foram mais elevados nos adenocarcinomas colorretais restritos à submucosa em relação às lesões polipóides com displasia de baixo grau, respectivamente (P < 0,001). Não foi encontrada diferença estatisticamente significativa na angiogênese entre os adenomas polipóides e não-polipóides através da quantificação 41,8 (15,8 - 71,9) vs 22 (16 - 40) e estimativa da extensão microvascular 24 (6,5-142,2) vs 17,5 (4,4-54,7), respectivamente. Conclusão: a utilização da análise digital de imagem e estereologia acrescentou maior objetividade e eficácia na metodologia de avaliação angiogênica, pois permitiu a precisa segmentação das áreas hipervasculares, a representação da morfologia tridimensional característica do suprimento vascular e a identificação de diferenças na microvascularização nas etapas evolutivas do câncer colorretal.

Análise da imagem digital para estimativa da área foliar em plantas de laranja Pêra

Objetivou-se, com o trabalho, avaliar dois métodos de estimativa da área foliar, em plantas de laranja Pêra, pela análise da imagem digital obtida com scanner e câmera fotográfica digital. Para determinar a área das folhas, um grupo de discos foi colocado sobre um leitor de scanner, sendo que a imagem obtida foi armazenada. Os mesmos grupos de discos foram fixados sobre cartolina branca e fotografados com câmera fotográfica digital. As imagens obtidas da câmera fotográfica e do scanner foram processadas utilizando ferramentas de um editor de imagem que permite a contagem de pixels de determinada cor, no caso verde. Para a comparação dos métodos, os discos foram submetidos a integrador óptico de área foliar modelo LICOR-3100, utilizando os mesmos agrupamentos. Foram coletadas 20 folhas (cinco em cada quadrante da planta) por parcela de um experimento para comparação de fertilizantes comerciais e doses de zinco, aplicados via foliar, em plantas de sete anos de idade. O experimento foi composto de sete tratamentos e quatro repetições, num total de 28 parcelas. Os dois métodos apresentaram alta correlação com a área estimada pelo integrador óptico de área, considerado como método de referência. O método da análise da imagem obtida com câmera fotográfica, na resolução de 5.0 megapixel, foi mais precisa quando comparada à área estimada pelo integrador óptico de área.