116 resultados para Image inpainting


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Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

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In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

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Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

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The presence of folded solution conformations in the peptides Boc-Ala-(Aib-Ala)2-OMe, Boc-Val-(Aib-Val) 2-OMe, Boc-Ala-(Aib-Ala)3-OMe and Boc-Val-(Aib-Val)3-OMe has been established by 270MHz 1H NMR. Intramolecularly H-bonded NH groups have been identified using temperature and solvent dependence of NH chemical shifts and paramagnetic radical induced broadening of NH resonances. Both pentapeptides adopt 310 helical conformations possessing 3 intramolecular H-bonds in CDCl3 and (CD3)2SO. The heptapeptides favour helical structures with 5 H-bonds in CDCl3. In (CD3)2SO only 4 H-bonds are readily detected.

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Lateral or transaxial truncation of cone-beam data can occur either due to the field of view limitation of the scanning apparatus or iregion-of-interest tomography. In this paper, we Suggest two new methods to handle lateral truncation in helical scan CT. It is seen that reconstruction with laterally truncated projection data, assuming it to be complete, gives severe artifacts which even penetrates into the field of view. A row-by-row data completion approach using linear prediction is introduced for helical scan truncated data. An extension of this technique known as windowed linear prediction approach is introduced. Efficacy of the two techniques are shown using simulation with standard phantoms. A quantitative image quality measure of the resulting reconstructed images are used to evaluate the performance of the proposed methods against an extension of a standard existing technique.

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A novel method, designated the holographic spectrum reconstruction (HSR) method, is proposed for achieving simultaneous display of the spectrum and image of an object in a single plane. A study of the scaling behaviour of both the spectrum and the image has been carried out and based on this study, it is demonstrated that a lensless coherent optical processor can be realized.

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In order to understand the molecular mechanism of non-oxidative decarboxylation of aromatic acids observed in microbial systems, 2,3 dihydroxybenzoic acid (DHBA) decarboxylase from Image Image was purified to homogeneity by affinity chromatography. The enzyme (Mr 120 kDa) had four identical subunits (28 kDa each) and was specific for DHBA. It had a pH optimum of 5.2 and Km was 0.34mM. The decarboxylation did not require any cofactors, nor did the enzyme had any pyruvoyl group at the active site. The carboxyl group and hydroxyl group in the Image -position were required for activity. The preliminary spectroscopic properties of the enzyme are also reported.

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Microsomes (105,000xg sediment) prepared from induced cells of Image was found to hydroxylate progesterone to 11a-hydroxyprogesterone (11a-OHP) in high yields (85-90% in 30 min.) in the presence of NADPH and O2. The pH optimum for the hydroxylase was found to be 7.7. However, for the isolation of active microsomes grinding of the mycelium should be carried out at pH 8.3. Metyrapone, carbon monoxide, SKF-525A, p-CMB and N-methyl maleimide inhibited the hydroxylase activity indicating the involvement of cytochrome P-450 system. The inhibition of the hydroxylase by cytochrome Image and the presence of high levels of NADPH-cytochrome Image reductase in induced microsomes suggest that the reductase could be one of the components in the hydroxylase system.

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A soluble fraction of Image catalyzed the hydroxylation of mandelic acid to Image -hydroxymandelic acid. The enzyme had a pH optimum of 5.4 and showed an absolute requirement for Fe2+, tetrahydropteridine, NADPH. Image -Hydroxymandelate, the product of the enzyme reaction was identified by paper chromatography, thin layer chromatography, UV and IR-spectra.

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tRNA isolated from . grown in a medium containing [75Se] sodium selenosulfate was converted to nucleosides and analysed for selenonucleosides on a phosphocellulose column. Upon chromatography of the nucleosides on phosphocellulose column, the radioactivity resolved into three peaks. The first peak consisted of free selenium and traces of undigested nucleotides. The second peak was identified as 4-selenouridine by co-chromatographing with an authentic sample of 4-selenouridine. The identity of the third peak was not established. The second and third peaks represented 93% and 7% of the selenium present in nucleosides respectively.

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An inducible Image -mandelate-4-hydroxylase has been partially purified from crude extracts of Pseudomonas convexa. This enzyme catalyzed the hydroxylation of Image -mandelic acid to 4-hydroxymandelic acid. It required tetrahydropteridine, NADPH, Fe2+, and O2 for its activity. The approximate molecular weight of the enzyme was assessed as 91,000 by gel filtration on Sephadex G-150. The enzyme was optimally active at pH 5.4 and 38 °C. A classical Michaelis-Menten kinetic pattern was observed with Image -mandelate, NADPH, and ferrous sulfate and Km values for these substrates were found to be 1 × 10−4, 1.9 × 10−4, and 4.7 × 10−5 Image , respectively. The enzyme is very specific for Image -mandelate as substrate. Thiol inhibitors inhibited the enzyme reaction, indicating that the sulfhydryl groups may be essential for the enzyme action. Treatment of the partially purified enzyme with denaturing agents inactivated the enzyme.

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Abstract is not available.

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We present a signal processing approach using discrete wavelet transform (DWT) for the generation of complex synthetic aperture radar (SAR) images at an arbitrary number of dyadic scales of resolution. The method is computationally efficient and is free from significant system-imposed limitations present in traditional subaperture-based multiresolution image formation. Problems due to aliasing associated with biorthogonal decomposition of the complex signals are addressed. The lifting scheme of DWT is adapted to handle complex signal approximations and employed to further enhance the computational efficiency. Multiresolution SAR images formed by the proposed method are presented.

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This paper presents a low cost but high resolution retinal image acquisition system of the human eye. The images acquired by a CMOS image sensor are communicated through the Universal Serial Bus (USB) interface to a personal computer for viewing and further processing. The image acquisition time was estimated to be 2.5 seconds. This system can also be used in telemedicine applications.

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In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.