Indian Journal of Science and Technology

Abstract

Objective: The main intention of this research is to protect the sharpness of image through decreasing the bit rates in compression image. The proposed approach also intends to improve the compression ratio by predicting the diagonal pixels along with the horizontal and vertical pixels of the image. Methods: In this research, Modified Hierarchical Prediction and Context Adaptive (MHPCA) coding is introduced to overcome the issue of enormous prediction error rate near edges and preserves the sharpness of images. MHPCA coding scheme considers the vertical, horizontal and diagonal (left up, left down and right up, right down) predictors to predict pixels of the image. The inclusion of diagonal predictor enhances the prediction accuracy of pixels in hierarchical prediction. Findings: The experimental tests of MHPCA are conducted and the performance is compared with the existing HPCA scheme which proves that the proposed methodology can preserve the sharpness of the image in an efficient manner than HPCA method. The comparison results prove that the proposed methodology is also efficient in terms of performance metrics such as 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.
Keywords: Context Adaptive Coding, Lossless Color Image Compression, Modified Hierarchical Prediction