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Satellite image resolution and brightness enhancement using discrete, stationary wavelet and singular value decomposition

机译:卫星图像分辨率和亮度增强使用离散,固定小波和奇异值分解

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Satellite images are used in the field of research and video processing applications. One of the main issues of satellite image interpretation is its low resolution. Resolution is defined as the smallest number of discriminable detail in an image. There are two types of resolution, grey level resolution and spatial resolution. Grey level resolution enhances the smallest discriminable details in an image, i.e. we can discriminate change in grey level. Images are being processed in order to obtain more enhanced resolution. The proposed image resolution enhancement technique is based on high frequency sub-band images obtained by discrete wavelet transform (DWT) of the input image. First of all interpolate the input image using bicubic interpolation then perform DWT on the interpolated input image to obtain different sub-bands. The high frequency subband's edges are enhanced using stationary wavelet (SWT). Combine these two high frequency subband's which are modified and interpolated. Then perform inverse DWT (IDWT) to get high resolution image. To increase the brightness of an image, use SVD (singular value decomposition) and DWT. The quantitative and visual results are showing the superiority of the proposed technique.
机译:卫星图像用于研究和视频处理应用领域。卫星图像解释的主要问题之一是其低分辨率。分辨率被定义为图像中最小数量的可辨别细节。分辨率有两种类型,灰度级分辨率和空间分辨率。灰度级分辨率增强了图像中最小的可辨别细节,即,我们可以区分灰度级别的变化。正在处理图像以获得更高的分辨率。所提出的图像分辨率增强技术基于输入图像的离散小波变换(DWT)获得的高频子带图像。首先使用双向插值地插入输入图像,然后在内插输入图像上执行DWT以获得不同的子带。使用静止小波(SWT)增强了高频子带的边缘。将这两个高频子带组合在修改和内插。然后执行逆DWT(IDWT)以获得高分辨率图像。为了增加图像的亮度,请使用SVD(奇异值分解)和DWT。定量和视觉结果显示了所提出的技术的优越性。

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