Low-Contrast Blurry Image Enhancement Based on Human Visual Property and Generalized Fuzzy Operator
On the basis of generalized fuzzy set theory, local contrast enhancement and human visual properties, a kind of adaptive enhancement technique presented. In this technique, first, a orthotropic Prewitt operator act on the original image, and then a normalization grads image can be obtained, second, we get the blurred image through a real-time low-pass filter such as Butterworth or Wavelet filter. At last we design a enhancement function based on a-tan function with the blurred image and grads image as input. And the gray image is translated to correspondent general membership function by using the a-tan mapping. The method can not only improve dynamic range, but also enhance the local contrast in the different gray levels with more image edges and details. Its efficiency and superiority are clarified by experiment.
Robin G. Qiu and Yongfeng Ju
H. F. Wang and P. Z. Liu, "Low-Contrast Blurry Image Enhancement Based on Human Visual Property and Generalized Fuzzy Operator", Applied Mechanics and Materials, Vols. 135-136, pp. 597-601, 2012