ABSTRACT
This chapter makes an attempt to throw sufficient light on the impact of evolutionary algorithms in some recent areas of image processing, and involves the design of a hardware efficient image filter. It also throws sufficient light on the design strategy of multiplier-less 2D filters with the aid of evolutionary computation techniques. More specifically, algorithms like differential evolution (DE) and self-organizing random immigrants genetic algorithm (SORIGA) had been employed for the design of such filters whose mask coefficients are represented in the form of the sum of signed powers-of-two. These filters have consequently been used to reduce the effect of Gaussian noise of different intensities from a few standard test images. Performance of these image denoising filters has been analyzed with respect to a few performance parameters, such as peak signal to noise ratio (PSNR), structural similarity index measure (SSIM), image enhancement factor (IEF), image quality index (IQI), and so on.
