Contrast Enhancement Image Fusion With Using Gaussian Filter (International Journal of Engineering and Computer Science, 2013)
Contrast enhancement has an important role in image processing applications. Conventional contrast enhancement techniques either often fail to produce satisfactory results for a broad variety of low-contrast images, or cannot be automatically applied to different images, because their parameters must be specified manually to produce a satisfactory result for a given image. This paper proposes a new automatic method for contrast enhancement with Gaussian Filter. The basic procedure is to first group the histogram components of a low-contrast image into a proper number of bins according to a selected criterion, then redistribute these bins uniformly over the grayscale, and finally ungroup the previously grouped gray-levels. The proposed approach is abbreviated as DACE/LIF. Two main stages are involved in the DACE/LIF approach: the conventional histogram equalization (CHE) and linear image fusion (LIF). Though the CHE has the problem of over enhancement, it is noted that the details which is not obvious in the original image are generally revealed after the CHE. Interesting enough, the details shown in the original image and in the equalized image are of a kind of complementary property.it is called detail complementary property (DCP) between the original image and the equalized image. The DCP suggests that the details in the original image and the equalized image may be combined to form an image with better contrast and visual quality. In the light of DCP, details are aware and the LIF is employed to combine the original image and its equalized image by the CHE. Simulation results indicate that the enhanced image by the proposed DACE/LIF with Gaussian approach has better visual quality than that in the original image