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New algorithm for infrared small target image enhancement based on wavelet transform and human visual properties

机译:基于小波变换和人眼视觉特性的红外小目标图像增强新算法

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The key to the wavelet based denoising techniques is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm (WDIDA), which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performance, preserving edges and improving the visual quality of images.
机译:基于小波去噪技术的关键是如何操纵小波系数。通过参考电路设计中的“或”概念,提出了一种新的小波域“或”降噪算法(WDIDA),该算法通过考虑相位或模量最大值来区分属于图像或噪声的小波系数。同时。使用这种新算法,可以改善去噪效果并减少计算时间。此外,为了增强图像的边缘而不放大噪声,根据人的视觉特性提出了一种对比度非线性增强算法。与传统的增强算法相比,我们提出的算法具有更好的降噪性能,保留边缘和提高图像的视觉质量。

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