Abstract
For human face images, the region of human face (ROHF) is considered to be the most important part, while the background is allowed to have degraded quality because it is considered to be less important. In this paper, a human face detection algorithm is combined with the set partitioning in hierarchical trees (SPIHT) algorithm for wavelet-based image coding. The human face detection algorithm is employed to automatically determine the ROHF in a human face image. The ROHF mask is generated in the wavelet domain. The wavelet coefficients in the ROHF mask of the LL subband are scaled to ensure that they are encoded with a higher priority. Finally the SPIHT algorithm is directly employed to encode the resulting coefficients progressively. Experimental results show that the ROHF exhibits much better quality than that of the background region at any bit rate. The encoded bitstream based on this approach is fully embedded and supports progressive transmission.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
