Image compression schemes facilitate the transmission and storage of data in an efficient form by reducing redundant image data in the case of limited transmission bandwidth or storage space. However, due to the irreversible nature of lossy compression, these schemes also introduce various types of color artifacts into the reconstructed image at a high compression ratio. Consequently, a change in color information affects the gamut characteristic of the reconstructed image. Accordingly, this article investigates the relationship between the compression ratio and the gamut variation for a reconstructed image using JPEG and JPEG2000. To analyze the relationship between the compression ratio and the gamut variation, 18 color samples from the Macbeth ColorChecker are initially used as representative colors for all colors due to their uniform distribution in CIELAB color space. Based on the color information shift for representative color samples, 12 natural color images, classified into two groups depending on four color attributes, are used to investigate the relationship between the level of compression and the variation in the gamut area for reconstructed images. After determining the gamut areas for the decompressed images in relation to the compression ratio, gamut fidelity is obtained using the ratio of unique colors relative to the gamut area. Finally, the optimal least square method is applied to obtain fitted curves as an equation minimizing the error between the real data, the gamut area for the decompressed images, and the corresponding approximated values.