1.1 Introduction to Contrast Enhancement: Image enhancement is a methodology of changing the pixel power of the information image for the purpose that the performance image is subjectively better [1]. The motivation behind image enhancement is to improve the interpretability or recognition of the data contained in the image for human viewers, or to provide "finer grained" information for other mechanized image preparation systems. 'pictures. Contrast enhancement is a valuable strategy for preparing investigative images, to enhance subtle elements of images that are over or under discovered. Contrast upgrading improves the detectable quality of elements in the scene by improving the distinction between items and their experiences. A high-difference image therefore encompasses the full range of light black level values; a low complexity image could be transformed into a high differentiation image by remapping or extending the ash level values ​​such that the histogram covers the entire scan. Contrast enhancements are routinely performed as a differential stretch mimicked by tonal enhancement, although these can both be achieved in a single step. Complexity stretching improves gloss contrasts consistently across the extent of image elements, while tonal enhancements improves gloss contrasts in shadow (dark), mid-tone (gray hair) areas or (bright) highlights at the expense of brightness contrasts in Alternative Neighborhoods Many image enhancement strategies have been proposed. An exceptionally well-known procedure for image enhancement is histogram equalization (HE). This method is normally used for image enhancement due to its simplicity and almost better processing on half of the paper......in frequency space it is necessary to improve image operations. image transformation. The comparison increment at this time could be expressed as follows: g(x,y) = T2{EH[T[f(x,y)]]} (1.1) The frequency enhancement routines are: pass filter -low, high pass filter, band pass and notch filtering and homomorphic filtering, etc. The result of homomorphic filtering is non-uniform light. The image in the dynamic range is not a clear image. The high-pass filter system reliably monitors part of the image and highlights points of interest. This can speak to high-frequency components, thus enhancing the part of the subtle edge element. This technique is suitable for detecting the outlines of objects in the image. Due to the low frequency method, the visual effect of the prepared image is not very good.