A spatial hue similarity measure for assessment of colourisation
This addresses the need for better evaluation metrics in colorization research, reducing reliance on subjective human inspection, but it is incremental as it builds on existing SSIM methods.
The paper tackled the problem of objectively assessing automatic colorization of grayscale images, which is ill-posed and multi-modal, by proposing a Spatial Hue Similarity Measure (SHSM) that penalizes spatially-incoherent modes and allows for qualitative and quantitative comparison of state-of-the-art methods.
Automatic colourisation of grey-scale images is an ill-posed multi-modal problem. Where full-reference images exist, objective performance measures rely on pixel-difference techniques such as MSE and PSNR. These measures penalise any plausible modes other than the reference ground-truth; They often fail to adequately penalise implausible modes if they are close in pixel distance to the ground-truth; As these are pixel-difference methods they cannot assess spatial coherency. We use the polar form of the a*b* channels from the CIEL*a*b* colour space to separate the multi-modal problems, which we confine to the hue channel, and the common-mode which applies to the chroma channel. We apply SSIM to the chroma channel but reformulate SSIM for the hue channel to a measure we call the Spatial Hue Similarity Measure (SHSM). This reformulation allows spatially-coherent hue channels to achieve a high score while penalising spatially-incoherent modes. This method allows qualitative and quantitative performance comparison of SOTA colourisation methods and reduces reliance on subjective human visual inspection.