Image restoration method in quantization guided by histogram restoration

This paper proposes a restoration method in quantization for the image with the reduced gray scale value. Since the vision systems are likely to capture images with insufficient contrast or with the reduced number of gray levels, some theoretical countermeasure must be introduced. From this reason, OK.QT (Oteru-Koshímizu's Quantization Theory) was introduced for providing the minimum quantization levels by which we can completely restore the full quantization levels of the histogram, or by which we can generate the super resolution in gray level. If no countermeasures are prepared, for example, the full potential of the display system cannot be utilized and furthermore the sufficient information in the gray value histogram cannot be provided for the sufficient performance of the image processing. This paper proposes an image restoration method in quantization guided by the histogram restoration. In this method, the histogram with sparse frequency is interpolates by using Sinc function, and we obtain the restored image by converting the gray scale values guided by the interpolated histogram.