Image representation is an active area of research due to its increasing applications in internet, military and defense. Image representation aims at representing an image with lesser number of coefficients than the actual image, without affecting the image quality. It is the first step in image compression. Once the image is represented by using some set of coefficients, it is further encoded using various compression algorithms. This paper proposes an adaptive method for image representation, which uses Slantlet transform and the concept of phase congruency, where the number of coefficients used for image representation depends on the information content in the input image. The efficiency of the proposed method has been assessed by comparing the number of coefficients used to represent the image using the proposed method with that used when Slantlet transform is used for image representation. The image quality is determined by computing the PSNR values and some commonly used existing quality metrics. Experiments carried out show highly promising results, in terms of the reduction in the number of coefficients used for image representation and the good visual quality of the resultant image.
A. T. and Dr. Latha Parameswaran, “A Method for Image Representation Using Slantlet Transform and Phase Congruency”, International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC. ACM New York, NY, 2014.