Image Compression Based on DCT and Adaptive Grid Scanning

Abstract

A lot of attentions has been paid by the researchers for lossy image compression. Due to the high uses of multimedia, a high image compression ratio while keeping good image quality, is still a research issue. In this paper, we proposed an image compression using adaptive scanning, in which DWT(discrete wavelet transform) is performed to source image, DCT(discrete cosine transform) is performed to obtained DWT elements. Next, non zero quantized DCT (discrete cosine transform) coefficients are represented in less number of bits. First, the source image is divided into $16\times 16$ grids and then DWT transformed, later the obtained elements are divided into $8\times 8$ grids and then DCT is performed, quantized, differential encoded and an indexed vector is formed from the quantized matrix using adaptive scanning. Furthermore the indexed vector is divided into two indexed vectors namely $nonzero$ vector and zerocount vector. The nonzero coefficients are stored in $nonzero$ vector and the number of zeros preceding a nonzero coefficient is stored in zerocount vector. A new block is introduced to store the number of bits required to store highest value of nonzero coefficient in $nonzero$ vector so that all the nonzero elements can be represented in that many bits rather than a fixed number of bits. The experimental results show that the proposed method has achieved more compression ratio with slight reduction in image quality as compared to existing recent methods.