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Existing methods either operate directly on RGB images or employ \\emph{heterogeneous} decompositions (\\eg, Fourier, wavelet) that redistribute spatial evidence across scale/frequency coefficients, making pixel-aligned cues less direct. We introduce a fundamentally different perspective: \\textbf{homogeneous image decomposition} via Retinex theory, which factorizes an image into illumination and reflectance components within the \\emph{same} spatial domain. 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