A spatial hue similarity measure for assessment of colourisation
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Residual Prior-driven Frequency-aware Network for Image Fusion
Cloud-Aware SAR Fusion for Enhanced Optical Sensing in Space Missions
BemaGANv2: A Tutorial and Comparative Survey of GAN-based Vocoders for Long-Term Audio Generation
SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping
MagCache: Fast Video Generation with Magnitude-Aware Cache
SSIMBaD: Sigma Scaling with SSIM-Guided Balanced Diffusion for AnimeFace Colorization
토론
이 논문과 연결된 포럼 글이 아직 없습니다.