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Gamma correction based satellite image enhancement using singular value decomposition and discrete wavelet transform

机译:基于奇异值分解和离散小波变换的基于伽玛校正的卫星图像增强

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This paper proposes the enhancement of low contrast satellite images based on intensity transformation. The intensity transformation is achieved using gamma correction on discrete wavelet transform (DWT) and the better illumination is achieved by singular value decomposition (SVD) technique. The DWT decomposes the input image in four different frequency sub-bands; low-low (LL), low-high (LH), high-low (HL) and high-high (HH). The gamma correction is applied only on LL sub-band to preserve the edge information. To improve the illumination, these gamma corrected LL sub-band information are passed through SVD. The enhanced image obtained is reconstructed by taking inverse discrete wavelet transform (IDWT). The performance measure is carried out in terms of EME, entropy and signals to noise ratio.
机译:本文提出了基于强度变换的低对比度卫星图像增强方法。使用离散小波变换(DWT)的伽马校正可实现强度变换,而奇异值分解(SVD)技术可实现更好的照明效果。 DWT在四个不同的子频带中分解输入图像。低-低(LL),低-高(LH),高-低(HL)和高-高(HH)。伽马校正仅应用于LL子带,以保留边缘信息。为了改善照明,这些经过伽玛校正的LL子带信息通过SVD传递。通过采用逆离散小波变换(IDWT)来重建获得的增强图像。性能评估是根据EME,熵和信噪比进行的。

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