Lossless JPEG

About: Lossless JPEG is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 51110 citations. The topic is also known as: Lossless JPEG & .jls.

Low-complexity approximation of 8-point discrete cosine transform for image compression

Abstract: In this paper the authors propose a new low-complexity approximation of 8-point discrete cosine transform (DCT) that requires 18 additions and two bit-shift operations. It is shown that the proposed transform outperforms significantly the known transform of the same computational complexity when applied to a JPEG compression stream in practical cases of encoding and decoding of still images. As such, the proposed transform can be effectively used in any practical applications where significant limitations exist regarding the computational capabilities coding and / or decoding devices, i.e. mobile devices or industrial imaging devices.

Identifying high quality JPEG compressed images through exhaustive recompression technique

Abstract: An important step in digital image forensics is to identify whether a given image is JPEG compressed or not. Most of state-of-the-art image forensic methods fail to differentiate between an uncompressed and a high quality compressed (near lossless) images. In this paper we propose a method to efficiently differentiate an original uncompressed image from high quality JPEG compressed images (but saved as TIFF or BMP) by analyzing the changes in the DCT coefficients after recompression. We define a new parameter and experimentally show that it acquires a very small value for uncompressed images compared to the JPEG compressed counterpart. Simulation results verify that the proposed method significantly outperforms other methods, for images taken from various sources.

A JPEG-based enhanced compression algorithm of digital holograms

Abstract: We present a modified version of the general JPEG encoder for digital holograms. Since digital holograms are characterized by most of their information concentrated at first-order term, to compress digital holograms only with their first-order term is available. The proposed algorithm performs 2D-DCT (discrete cosine transform) on digital holograms as the general JPEG, then quantizes and encodes the low-frequency section extracted with an adaptive mask. Compatible with the general JPEG, the compressed holograms can be directly decoded by the general decoders. Our simulation and experimental results show that this algorithm has higher compression ratio than the general JPEG and more accurate retrieved phase while the compression is equal.