Advanced Image Coding and its Comparison with Various Still Image Codecs

JPEG is a popular DCT-based still image compression standard, which has played an important role in image storage and transmission since its development. Advanced Image Coding (AIC) is a still image compression system which combines the intra frame block prediction from H.264 with a JPEG-based discrete cosine transform followed by context adaptive binary arithmetic coding (CABAC), with best performance at low bit rates and has better performance than JPEG overall. In this paper, we propose a modified AIC (M-AIC) by replacing the CABAC in AIC with a Huffman coder and an adaptive arithmetic coder. The results were compared with other image compression techniques like JPEG using baseline method and JPEG2000, JPEG-LS and JPEG-XR in lossy compression, on various sets of test images. Simulation results are evaluated in terms of bit-rate, quality- PSNR and structural similarity index (SSIM). The simulation results based on PSNR demonstrate that M-AIC has optimal performance for images of all resolutions. The performance of still image codecs like M-AIC, JPEG-LS and JPEG-XR does not depend on the image resolution, which makes them suitable for wide varieties of applications. SSIM simulation results illustrate that M-AIC, JPEG2000 and JPEG-XR have similar performance and are better than any other codecs.