Fuzzy C-means-based JPEG algorithm for still image compression

Abstract

The magnitude of information that is conveyed via the Internet has escalated more rapidly during the last few decades. Image compression provides an appreciable way to dwindle the image size. For the conservation of bandwidth during still image compression, JPEG is advisable. As one can gather and communicate the images early with reduced size, we planned an innovative JPEG compression algorithm (de Queiroz, Member IEEE, IEEE Trans Image Process 7(12):1661−1672, 1998, [1] Prakash, IEEE Member, Mitchell, IEEE Fellow, Stepneski, IEEE Int Conf Image Process 3:494−497, 2001, [2], Sreelekha, Sathidevi, An improved JPEG compression scheme using human visual system model, 2007, [3]) with fuzzy c-means-based clustering in this work. The anticipated algorithm produces enhanced results in comparison with standard algorithms in the form of some estimation parameters like MSE, PSNR, and quantity of bits transmitted (Egger, Li, IEEE Int Conf Image Process 3:326−330, 1994, [4]). The speed is increased with the proposed JPEG algorithm, thereby diminishing the memory that is necessary for hoarding the encoded bits. The reassembled image after decompression is as similar as the image which was sent as an input.