OPTIMAL IMPLEMENTATION ON FPGAs BASED ON WAVELET TRANSFORM AND SELF ORGANIZING MAP FOR MEDICAL IMAGES COMPRESSION

Abstract

Medical images present specific characteristics which require to be exploited by an explicit and efficient compression algorithm. The Vector Quantization (VQ) constitutes a crucial stage in lossless Digital images compression where it allows to create a dictionary on the level "block" by a neuronal approach that of Kohonen (Self Organizing Map : SOM) which is widely used in implementation of FPGA circuits for medical image compression
applications. This paper is devoted to the implementation of a new combined method based on wavelet transform and neurons network (WT-SOM) and designed for the implementation on FPGA for medical images compression applications. Simulation results show the effectiveness of our proposed method.