A New Proposed Method For A Statistical Rules-Based Digital Image Compression

Abstract

Abstract Image compression depends on data compression of digital images. Its central objective is to decrease the redundancy of the image data for reducing space and the cost of transmitting data in public communication channels. This research suggests a new compression technique based on the statistical rules. The proposed technique is one of the lossy compression techniques is based upon the statistics of the pixel values of the gray-scale image. The quality of these compressed images have been evaluated using some factors like the Image size before/after the compression process, Compression Ratio, (CR), and Peak Signal to Noise Ratio, (PSNR), Mean Square Error (MSE), and Mean Space Saving (MSS). Experimental results have demonstrated that the proposed technique provides sufficient higher compression with minimal to lose data.