This paper presents RIFD-DLT, an advanced near-lossless image compression algorithm that combines Delta Encoding with the original rounding the intensity followed by division (RIFD) method. The RIFD method first minimizes the image intensities, which makes the next compression stages more efficient. Subsequently, Delta Encoding subtracts neighboring rows in each of the image's three-color matrices, using the proximity of pixel values in adjacent rows to further reduce the image intensity. Extensive investigations show that RIFD-DLT outperforms the state-of-the-art algorithms and benchmarks with respect to compression ratio and processing time. More specifically, RIFD-DLT compresses data from 11520 KBs to 2131 KBs with an 81.93% reduction and a 43.7% improvement over original RIFD-Huffman when compressing Kodak Image set. When comparing the RIFD-DLT with LICA algorithm, the total file size is reduced by 71.2%, representing a 10.73% improvement for RIFD-DLT. Also, RIFD-DLT shows notable speed gains over RIFD-Huffman, requiring only 34.62 seconds to compress and decompress all images from three datasets (Waterloo, Kodak and EPFL), as compared to 50.99 seconds for RIFD-Huffman. As for the image quality, the proposed algorithm achieved an average PSNR values of 58.51 dB, 51.3 dB, and 52.22 dB for the EPFL, Kodak, and Waterloo image sets, respectively, demonstrate the excellent image quality that persists after decompression, with a minimal distortion that is imperceptible to the human visual system and identically to the RIFD-Huffman PSNR. These findings show that, while preserving excellent image quality, RIFD-DLT provides an incredibly efficient and fast method of image compression.