調(diào)色盤操作實(shí)例(編輯修改稿)
2024-08-18 01:25 本頁面
【文章內(nèi)容簡介】 of sk using the iterative scheme defined in connection with Eq. (). 5) For each pixel in the original image, if the value of that pixel is rk, map this value to its corresponding level sk。 then map level sk into the final level zk. Use the preputed values from Steps (2) and (4) for these mappings. ? Step (5) implements two mappings. The first mapping is nothing more than histogram equalization. Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Original Image Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Fail to Histogram Equalization Since the problem with the transformation function in Fig. (a) was caused by a large concentration of pixels in the original image with levels near 0. Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Good Result by Histogram Matching Method Manually specified function G(z) G1(z) Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Discussion of Histogram Matching ? Histogram specification is a trialanderror process. ? In general, there are no rules for specifying histograms, and one must resort to analysis on a casebycase basis for any given enhancement task. Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Local Enhancement ? The histogram equalization and histogram matching is the global processing, that is, the pixels are modified by a transformation function based on the graylevel content of an entire image. ? It is also necessary to enhance details over small areas in an image. ? The solution is to devise transformation functions based on the graylevel distribution in the neighborhood of every pixel in the image. Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Local Enhancement Example Digital Image Processing, 2nd ed. 169。 2022 R. C. Gonzalez amp。 R. E. Woods Use of Histogram
規(guī)章制度相關(guān)推薦
鄂ICP備17016276號-1