Abstract: Images are increasingly displayed at a range of devices linked by scattered networks, which place bandwidth constraints on image transmission. Since imaging has transitioned to digital formats, most favorable settings are needed for image compression. It is feasible to apply lossy JPEG compression to images without compromise of image quality. Quantization table in JPEG decides a degree of compression that reduces the file size significantly, but produces a scale of image distortion that is not vital. Designing of quantization table in JPEG is an optimization problem. For the past decades, numerous research efforts have been concentrated in this particular area. In mid-2000, a new epoch was started, meta-heuristics for solving this problem. Nature inspired algorithms are meta-heuristics that mimic the nature for solving optimization problems. The real beauty of nature inspired algorithms lie in the fact that it receives its sole inspiration from nature. This paper gives an extensive review of some major nature inspired meta-heuristic algorithms such as Genetic Algorithm, Differential Evolution, Particle Swarm Optimization and Firefly Algorithm for optimizing quantization table in JPEG baseline algorithm. Further, key issues involved in solving this problem for these meta-heuristics algorithms are also discussed.
Keywords: Image compression, JPEG, quantization table, optimization problem, Nature inspired algorithms, meta-heuristics algorithms.