PerSIM: Multi-resolution Image Quality Assessment in the Perceptually Uniform Color Domain
This work addresses image quality assessment for applications like compression and display, but it is incremental as it builds on existing perceptual models and databases.
The authors tackled the problem of objective image quality assessment by modeling human visual system characteristics and color similarity in a perceptually uniform color domain, resulting in PerSIM outperforming all compared metrics on LIVE and TID2013 databases in terms of ranking, monotonic behavior, and linearity.
An average observer perceives the world in color instead of black and white. Moreover, the visual system focuses on structures and segments instead of individual pixels. Based on these observations, we propose a full reference objective image quality metric modeling visual system characteristics and chroma similarity in the perceptually uniform color domain (Lab). Laplacian of Gaussian features are obtained in the L channel to model the retinal ganglion cells in human visual system and color similarity is calculated over the a and b channels. In the proposed perceptual similarity index (PerSIM), a multi-resolution approach is followed to mimic the hierarchical nature of human visual system. LIVE and TID2013 databases are used in the validation and PerSIM outperforms all the compared metrics in the overall databases in terms of ranking, monotonic behavior and linearity.