Publication

Abstract : Nowadays, many researchers are attracted by image compression techniques because of the minimization of storage and transmission cost over the internet. The main objective of image compression is to reduce the redundant and irrelevant information from the original data. Haar Wavelet Transformation (HWT) is an efficient transform coding among the lossy image transform techniques. This proposed work has two stages of process: Vector Quantization and Thresholding. In the first stage, Haar Wavelet Transformation is implemented which results categorized into two matrices; Approximation Co-efficient (AC) matrix and Detailed Coefficient (DC) matrices. The second stage of proposed method is applied Vector Quantization(VQ) to improve the compression efficiency. This proposed work achieved higher compression ratio without compromising the image quality. The performance of the proposed method is compared using the traditional Haar Wavelet transform based method which has been evaluated using some popular parameters such as Peak Signal to Noise Ratio (PSNR), Structural Similarity Index(SSIM), Compression Ratio (CR) and Bit Rate(BR). The computation cost is minimized using proposed method. The comparative analysis of the proposed method has witnessed the achievement of good compression ratio and image quality as well.