Analysis of Remote Sensing Image Super Resolution using Fluid Lenses

In this thesis, a study of both hardware and software solutions for image enhance¬ment has been done. On the hardware side, a new liquid lens design with a DESA membrane located directly in the optical path has been demonstrated. Two pro¬totypes with two different DESA, which have a 40 and 20 mm active area in diameter, were developed. The lens performance was consistent with the mechan¬ics of elastomer deformation and relative focal length changes. A laser beam was used to show the change in the meniscus and to measure the focal length of the lens. The experimental results demonstrate that voltage in the range of 50 to 750 V is required to create change in the meniscus. On the software side, a new satellite image enhancement system was proposed. The proposed technique decomposed the noisy input image into various frequency subbands by using DT-CWT. After removing the noise by applying the LA-BSF technique, its resolution was enhanced by employing DWT and interpolating the high-frequency subband images. An original image was interpolated with half of the interpolation factor used for interpolating the high-frequency subband images, and the super-resolved image was reconstructed by using IDWT. A novel single-image SR method based on a generating dictionary from pairs of HR and their corresponding LR images was proposed. Firstly, HR and LR pairs were divided into patches in order to make HR and LR dictionaries respectively. The initial HR representation of an input LR image was calculated by combining the HR patches. These HR patches are chosen from the HR dictionary corre-sponding to the LR patches that have the closest distance to the patches of the in¬put LR image. Each selected HR patch was processed further by passing through an illumination enhancement processing order to reduce the noticeable change of illumination between neighbor patches in the super-resolved image. In order to reduce the blocking effect, the average of the obtained SR image and the bicubic interpolated image was calculated. The new kernels for sampling have also been proposed. The kernels can improve the SR by resulting in a sharper image. In order to demonstrate the effectiveness of the proposed kernels, the techniques from [83] and [50] for resolution enhance¬ment were adopted. The super-resolved image was achieved by combining the HR images produced by each of the proposed kernels using the alpha blending tech-nique. The proposed techniques and kernels are compared with various conventional and state-of-the-art techniques, and the quantitative test results and visual results on the final image quality show the superiority of the proposed techniques and ker¬nels over conventional and state-of-art techniques

Data augmentation from RGB to chlorophyll fluorescence imaging Application to leaf segmentation of Arabidopsis thaliana from top view images

Résumé en françai

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks

Robust non-blind color video watermarking using QR decomposition and entropy analysis

Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks

Wavelet transform based new interpolation technique for satellite image resolution enhancement

In this research paper, we propose a new interpolation technique based on the Stationary Wavelet Transform (SWT) and iterative back projection (IBP) for satellite images. Firstly the low resolution image is interpolated by using bicubic interpolation and then decomposed into different subband images by SWT. Each subband is decimated to four lower low resolution images. The four low resolution images are interpolated and registered by using bicubic interpolation and IBP respectively. Inverse SWT (ISWT) is used to generate a Super-resolved output image. The proposed interpolation technique has been tested on several remote sensing images. The quantitative PSNR and SSIM results as well as the visual results show the superiority of the proposed interpolation technique over the other interpolation and image resolution enhancement techniques. For one of the images the PSNR of the proposed method has achieved 3.84dB, 2.11dB, and 1.1dB more improvements than bicubic interpolation, Irani and Peleg technique, and Wavlet Zero Padding technique respectively

Statistical approach based iris recognition using local binary pattern

Among biometric features utilized for identity recognition purposes, iris has proven to be the most reliable one in terms of sufficient distinctiveness, which has direct implications and importance towards improving the performance and safety of the security verification process through which it is decided whether any instance at hand should be granted permission to access preserved locations or sources of information. This paper deals with the main challenge involved in iris recognition, which lies in its comparatively high computational complexity, having remained unresolved heretofore, at least, as far as the existing literature is concerned. The enhancement brought about by the proposed methodology originates from taking advantage of local binary patterns for processing each segment of the original image, having undergone equalization in advance, as well as applying probability distribution functions separately to every layer of the pixel values, whereas being represented with respect to mutually-independent hue-saturation-intensity color channels. Besides, the Kullback-Leibler Distance between the vectors obtained through concatenation of the feature vectors is taken into account as the classification criterion, which has led to an outstanding recognition rate of 98.44 percent when tested on the UPOL database, with 192 iris images

Colour image watermarking based on wavelet and QR decomposition

In this work, a new image watermarking algorithm on colour images is proposed. The proposed algorithm divides a cover image into three colour bands of red, green and blue. Then the following tasks are done on all three channels separately. First, Each colour band is divided into patches of small sizes then the entropy of each patch is calculated. At this step a threshold is found based on the average entropy of all patches and following is applied to all patches which have entropy lower than the threshold. A wavelet representation of each patch are given by applying a discrete wavelet transform. Then Singular value decomposition, orthogonal-triangular decomposition, and a chirp z-transform are used to embed a watermark on the cover image. Several signal processing attacks are applied on watermarked images in order to robustness of the algorithm. The Proposed algorithm is compared with one conventional and two state-of-the-art algorithms. Experimental results show superiority of the proposed algorithm compare with other algorithm in the area of image watermarking

A new low-complexity patch-based image super-resolution

In this study, a novel single image super-resolution (SR) method, which uses a generated dictionary from pairs of high-resolution (HR) images and their corresponding low-resolution (LR) representations, is proposed. First, HR and LR dictionaries are created by dividing HR and LR images into patches Afterwards, when performing SR, the distance between every patch of the input LR image and those of available LR patches in the LR dictionary are calculated. The minimum distance between the input LR patch and those in the LR dictionary is taken, and its counterpart from the HR dictionary will be passed through an illumination enhancement process resulting in consistency of illumination between neighbour patches. This process is applied to all patches of the LR image. Finally, in order to remove the blocking effect caused by merging the patches, an average of the obtained HR image and the interpolated image is calculated. Furthermore, it is shown that the stabe of dictionaries is reducible to a great degree. The speed of the system is improved by 62.5%. The quantitative and qualitative analyses of the experimental results show the superiority of the proposed technique over the conventional and state-of-the-art methods

Demystifying deep learning for medical physicists

Résumé en français

Improved Iterative Back Projection for video super-resolution

In this paper, Iterative Back Projection (IBP) technique is improved by using bicubic resampling. The improvement in the performance is achieved by adding bicubic interpolation followed by bicubic decimation in each iteration of IBP. Firstly the four low resolution frames are considered as observed frames. The size of the reference frame is increased by interpolation to generate the initial guess frame. Then the size of interpolated frame is increased and decreased respectively by using bicubic interpolation and decimation processes. This operation generates a lower bandwidth in the frequency domain, smoothing the impulsive errors in the respective consecutive frames reducing the mean square error in each iteration. The proposed method has been tested on Akiyo, Carphone, Mother & Daughter, and Miss-America video sequences. The quantitative peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) results as well as the visual results show the improvement obtained by the proposed technique on the standard IBP