Since the details in quasi-homogeneous region will be degraded from a conventional global image enhancement methods such as histogram equalization. This degradation causes from the saturation of the gray levels in equalization process. Then the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the regions. To obtain the quasi-homogeneous regions the image can be segmented by using a watershed transform. The watershed transform is based on mathematical morphology; therefore the segmented regions can be effectively separated meaningful. Two adjacent regions in images which almost similar in gray levels can be separted by the watershed transform. In the color image enhancement three spectral bands are enhanced independently. Then all the three bands are assigned to each processed image in order to produce a color composite image. By the proposed algorithm the result images show the better perception on image details. Therefore the high efficiency of image classification can be obtained by using this color image.

Currently competition in terms of resolution and contrast of photos from digital cameras are widely mentioned. The higher resolution the photos contain; the more details the picture has. This fact enables the more details of pictures which also hold much more capacity of data. This also causes the electronic devices to be updated all the time to cope with those problems. Therefore the conventional devices are obsolete. This research has been developed and applied to improve digital photos with high contrast. The researcher has solved the problems by keeping the average error of the lowest results and improving heat histogram of various curves. The heat will break the histogram of the original image into n part by the concave side of the heat histogram. The part of this histogram is equal to n+1 and then smooth each other heap histogram independently. The result showed that the Tennengrade or contrast of the image is higher than the original one. However it can retain brightness errors (AMBE) as well