A new nonlinear quantizer for image processing within nonextensive statistics

In this study, we introduce a new nonlinear quantizer for image processing by using Tsallis entropy. Lloyd-Max quantizer is commonly used in minimizing the quantization errors. We report that the new introduced technique works better than Lloyd-Max one for selected standard images and could be an alternative way to minimize the quantization errors for image processing. We, therefore, hopefully expect that the new quantizer could be a useful tool for all the remaining process after image quantization, such as coding (lossy and lossless compression).