Rewritable data embedding in image based on improved coefficient recovery
Document Type
Conference Item
Publication Date
1-1-2021
Abstract
Nowadays, most images are stored and transmitted in certain compressed forms based on some coding standards. Usually, the image is transformed, e.g., by discrete cosine transformation, and hence coefficient makes up a large proportion of the compressed bit stream. However, these coefficients might be corrupted or completely lost due to transmission errors or damages incurred on the storage device. Therefore, in this work, we aim to improve a conventional coefficient recovery method. Specifically, instead of using the Otsu's method adopted in the conventional method, an adaptive segmentation method is utilized to split the image into background and foreground regions, forming non-overlapping patches. Missing coefficients in these non-overlapping patches are recovered independently. In addition, a rewritable data embedding method is put forward by judiciously selecting patches to embed data. Experiments are carried to verify the basic performance of the proposed methods. In the best-case scenario, an improvement of 31.32 in terms of CPU time is observed, while up to 7149 bits of external data can be embedded into the image. © 2021 IEEE
Keywords
Embeddings, Image coding, Image enhancement, Image segmentation, Recovery, Virtual storage, Adaptive, Bitstreams, Coding standards, Coefficient recovery, Data embedding, DCT, Discrete cosine transformation, Image-based, Rewritable, Segmentation, Discrete cosine transforms
Divisions
Software
Funders
Ministry of Higher Education, Malaysia [Grant No: FRGS/1/2018/ICT02/MUSM/02/2]
Publication Title
Proceedings of the 2021 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2021
Event Title
Proceedings of the 2021 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2021
Event Location
Virtual, Online
Event Dates
13-15 September 2021
Event Type
conference