Low Complexity Gray-scale Image Compression Method Using Index-Based Approach

Images consume more space when stored and use a lot of bandwidth during transmission. Hence, an image compression reduces storage space required, and time to transmit an image by making effective usage of bandwidth. In this paper, a simple image compression method using an index-based approach is proposed. This approach makes use of simple indices of an array to compress images. The context of nearby fifteen pixels is used, and the index for the current pixel is found. The indices are found for every pixel of an image. These indices are transformed and written into a transformed file. This transformed file is further compressed with Huffman compression to achieve a compressed file. Decompression uses a simple methodology to reconstruct the image. The pixel value is reconstructed using the index, and from previously reconstructed pixels of the image. The proposed algorithm provides high fidelity images at lower Peak Signal to Noise Ratio (PSNR). The results obtained from the proposed algorithm are compared with JPEG algorithm. At the same PSNR values, the quality of the reconstructed images by the proposed algorithm is comparable to that of the JPEG algorithm.