Evaluation and Comparison of DDBTC using HVPSNR

Abstract: Image compression is the technique used to reduce irrelevance and redundancy of the image data in order to be able to store as well as transmit data in an efficient form. Image compression techniques may be lossy or lossless. Among the various image compression techniques, BTC [Block Truncation Coding] belongs to lossy type of image compression technique especially for greyscale images. The procedure consists of steps which divides the original image into various blocks and then uses quantizers to reduce the number of grey levels in each block while maintaining the same mean and standard deviation. BTC technique is a quite old technique but a highly efficient compression technique. BTC suffers from certain key problems such as inherent artifacts, blocking effect and false contour. Through the proposed DDBTC method, namely Dot-Diffused BTC (DDBTC), we try to deal with those problems. The parallelism process of the dot diffusion is properly exploited to provide excellent processing efficiency. Similarly, excellent image quality is assured through co-optimizing the class matrix and diffused matrix of the dot diffusion. According to the experimental results using HVPSNR [Human-Visual Peak Signal-To-Noise Ratio], the proposed DDBTC is found to be superior to the original BTC techniques. Keywords: Image Compression, DDBTC, HVPSNR, Dot Diffused, False contour.