Image Compression Based on a Novel Fuzzy Learning Vector Quantization Algorithm
نویسندگان
چکیده
We introduce a novel fuzzy learning vector quantization algorithm for image compression. The design procedure of this algorithm encompasses two basic issues. Firstly, a modified objective function of the fuzzy c-means algorithm is reformulated and then is minimized by means of an iterative gradient-descent procedure. Secondly, the training procedure is equipped with a systematic strategy to accomplish a smooth transition from fuzzy mode, where each training vector is assigned to more than one codebook vectors, to crisp mode, where each training vector is assigned to only one codebook vector.
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