Parametric-oriented fitting for local contrast enhancement

A POSHE-Based Optimum Clip-Limit Contrast Enhancement Method for Ultrasonic Logging Images

“…They are the mean gradient (MG) [ 45 ] and mean structural similarity index (MSSIM) [ 76 ]. MG is considered as one of the most robust and functionally accurate image quality measures [ 45 , 71 , 72 ] and is defined by where denotes the image gradient magnitude at pixel ( i , j ), which is calculated within a local 3 × 3 square window using the Sobel operators, and M × N is the image size. In general, MG rises when both the quantity and intensity of gradients of an image increase; a large MG indicates the image has strong local contrast or texture variation, However, MG that is too high is often accompanied by an unnatural look because of over-enhancement and the quality of the image is decreased.…”

“…In addition, HE may also cause loss of details since some gray levels with a smaller proportion pixel number are combined to form a certain gray level [ 49 ]. To avoid shortcomings of the classic HE, many techniques and improved algorithms on the basis of histogram equalization have been proposed in the past and have been widely utilized in the field of image enhancement [ 41 , 42 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 ]. Since preservation of the original brightness is crucial to avoid undesirable artifacts, the brightness preserving bi-histogram equalization (BBHE) [ 50 ] is developed to preserve the original brightness to a certain extent by individually equalizing two sub-histograms based on the mean value of the images.…”