Efficient Lossless Image Compression using Modified Hierarchical Forecast and Context Adaptive System

Objective: The main intention of this investigation is to protect the sharpness of image through decreasing the bit rates in compression image. Also this scenario intends to accomplish the high compression ratio by using the lossless compression approaches. Methods: In this research, Hierarchical Forecast and Context Adaptive systems are introduced to provide the lossless compression color image. Modified Hierarchical Prediction Scheme is enhanced which overcomes the issue of enormous prediction error rate near edges and preserves the sharpness of images. This scenario considers the vertical, horizontal and diagonal (left up, left down and right up, right down) predictors to predict pixels. Diagonal predictor enhances the perdition accuracy of pixels in Hierarchical Prediction. Findings: In this work the methods used namely Context Adaptive Coding and Modified Hierarchical Prediction Scheme are used to preserve the sharpness of an image. The experimental tests conducted were proves that the proposed methodology can preserve the sharpness of the image efficiently rather than existing method. The experimental results of this work prove that the proposed methodology is improved in terms of all performance metrics called Bits Per Pixel (BPP), Compression Ratio, Mean Square Error rate (MSE) and Peak Signal to Noise Ratio (PSNR). Application/Improvement: The findings demonstrate that by using proposed MHPCA scheme the bit rates in compressed images are reduced significantly which preserves the sharpness of the image. MHPCA coding scheme also reduces the error rate considerably and produces higher compression ratio than the existing HPCA scheme.