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Image Contrast Enhancement by Homomorphic Filtering based Parametric Fuzzy Transform

机译:基于同型滤波的参数模糊变换的图像对比度增强

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In this paper, a new image contrast enhancement technique by taking the advantages of Homomorphic decomposition and fuzzy transform is been employed. For increasing the clarity of the image generally, histogram or Retinex theory based algorithms were used. These procedures worked on enhancing the reflectance layer by ignoring illumination, which is not a better strategy and leads to poor results. Fuzzy based image enhancement approach makes use of illumination by omitting reflectance. In our proposed algorithm, Homomorphic decomposition is used for getting the exact illumination image from the value layer of HSV (Hue, Saturation, Value) image. Next, the parametric fuzzy transform is employed to enhance the image by updating its membership functions and thereby smoothing the luminance layer. Finally, a weighted image is generated by pixel neighborhood property for preserving the image details. The results show the profoundness of the algorithm in terms of its clarity and complexity even for nonuniform illumination images.
机译:本文采用了一种新的图像对比增强技术,采用具有同态分解和模糊变换的优点。为了提高图像的清晰度,通常使用基于直方图或视网膜理论的算法。这些程序在通过忽略照明来增强反射率层,这不是更好的策略并导致结果不佳。基于模糊的图像增强方法通过省略反射率利用照明。在我们所提出的算法中,同性恋分解用于从HSV(色调,饱和度,值)图像的值层来获得精确的照明图像。接下来,采用参数模糊变换来通过更新其隶属函数并从而平滑亮度层来增强图像。最后,通过像素邻域属性生成加权图像,以保留图像细节。结果表明,即使对于非均匀照明图像,也表明了算法的深刻性和算法。

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