Compressing Sign Information in DCT-based Image Coding via Deep Sign Retrieval
This work addresses a specific bottleneck in image compression for applications like storage and transmission, offering an incremental improvement over existing techniques.
The paper tackles the problem of compressing sign information of DCT coefficients in image coding, which is challenging due to equiprobable signs, by proposing a deep sign retrieval method that excludes signs from the bitstream and recovers them at the decoder, resulting in reduced bit amount and computation cost compared to previous methods.
Compressing the sign information of discrete cosine transform (DCT) coefficients is an intractable problem in image coding schemes due to the equiprobable characteristics of the signs. To overcome this difficulty, we propose an efficient compression method for the sign information called "sign retrieval." This method is inspired by phase retrieval, which is a classical signal restoration problem of finding the phase information of discrete Fourier transform coefficients from their magnitudes. The sign information of all DCT coefficients is excluded from a bitstream at the encoder and is complemented at the decoder through our sign retrieval method. We show through experiments that our method outperforms previous ones in terms of the bit amount for the signs and computation cost. Our method, implemented in Python language, is available from https://github.com/ctsutake/dsr.