  In perceptual image coding applications, the main objective is to decrease,
as much as possible, Bits Per Pixel (BPP) while avoiding noticeable distortions
in the reconstructed image. In this paper, we propose a novel perceptual image
coding technique, named Perceptual Color Compression (PCC). PCC is based on a
novel model related to Human Visual System (HVS) spectral sensitivity and
CIELAB Just Noticeable Color Difference (JNCD). We utilize this modeling to
capitalize on the inability of the HVS to perceptually differentiate photons in
very similar wavelength bands (e.g., distinguishing very similar shades of a
particular color or different colors that look similar). The proposed PCC
technique can be used with RGB (4:4:4) image data of various bit depths and
spatial resolutions. In the evaluations, we compare the proposed PCC technique
with a set of reference methods including Versatile Video Coding (VVC) and High
Efficiency Video Coding (HEVC) in addition to two other recently proposed
algorithms. Our PCC method attains considerable BPP reductions compared with
all four reference techniques including, on average, 52.6% BPP reductions
compared with VVC (VVC in All Intra still image coding mode). Regarding image
perceptual reconstruction quality, PCC achieves a score of SSIM = 0.99 in all
tests in addition to a score of MS-SSIM = 0.99 in all but one test. Moreover,
MOS = 5 is attained in 75% of subjective evaluation assessments conducted.
