Lossless image compression using multi-band prediction for visible and infrared spectra

This study focuses on lossless coding of still images utilizing multimodal signals. Instead of limiting the analysis to a single modality, the aim is to improve coding efficiency by exploiting correlations between different modalities. The experiments target the encoding of infrared images and their corresponding visible light images (grayscale images), with the objective of achieving more efficient coding by using the infrared image as auxiliary data for the grayscale image, rather than encoding them separately. Specifically, two encoding methods are applied to the grayscale image: single-modal encoding and encoding using multimodal data as auxiliary information. The method with the highest efficiency is selected. Experimental results on 157 images demonstrate that the proposed method reduces the encoded size by 4.25% compared to single-modal encoding. The gain of 4.25% achieved by the proposed method is significantly higher compared to the 2–3% reported in previous method.