Image communication system design based on the structural similarity index

Channappayya, Sumohana S., 1977-
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The amount of digital image and video content being generated and shared has grown explosively in the recent past. The primary goal of image and video communication systems is to achieve the best possible visual quality at a given rate constraint and channel conditions. In this dissertation, the focus is limited to image communication systems. In order to optimize the components of the communication system to maximize perceptual quality, it is important to use a good measure of quality. Even though this fact has been long recognized, the mean squared error (MSE), which is not the best measure of perceptual quality, has been a popular choice in the design of various components of an image communication system. Recent developments in the field of image quality assessment (IQA) have resulted in the development of powerful new algorithms. A few of these new algorithms include the structural similarity (SSIM) index, the visual information fidelity (VIF) criterion, and the visual signal to noise ratio (VSNR). The SSIM index is considered in this dissertation. I demonstrate that optimizing image processing algorithms for the SSIM index does indeed result in an improvement in the perceptual quality of the processed images. All the comparisons in this thesis are made against appropriate MSE-optimal equivalents. First, an SSIM-optimal linear estimator is derived and applied to the problem of image denoising. An algorithm for SSIM-optimal linear equalization is developed and applied to the problem of image restoration. Followed by the development of the linear solution, I addressed the problem of SSIM-optimal soft thresholding which is a nonlinear technique. The estimation, equalization, and soft-thresholding results all show a gain in the visual quality compared to their MSE-optimal counterparts. These solutions are typically used at the receiver of an image communication system. On the transmitter side of the system, bounds on the SSIM index as a function of the rate allocated to a uniform quantizer are derived.