NEW HISTOGRAM MODIFICATION BASED ON IMAGE EDGE MODEL

In this paper, a new histogram modification method is introduced, which is based on the image edge model and noise model. Its main consideration is using the image edge model and noise model to detect the boundary between object and background, and then choosing the pixels sited in the left and right side of the boundary, or pixels sited in the boundary, to build the histogram. With this method, in the histogram, the number of pixels in object is approximately equal to the number of pixels in background. This new method can avoid the defects of losing small object in conventional histograms, such as edge intensity weighted histogram, histogram of interior pixels and histogram of whole pixels, and can avoid the defects of sensitive to noise and threshold depending on the model of edge in the histogram of pixels having high edge values. The new histogram is very general and practical, which can be used for the threshold selection when the object is big or small and the edge model is ramp like or roof as well. Experiments prove that this new method is rather better than others. In recently years, little literature is found in the field of histogram modification, and this new method makes a big improvement.