A survey on automatic techniques for enhancement and analysis of digital photography

Abstract

The fast growth in the consumer digital photography industry during the past decade has led to the acquisition and storage of large personal and public digital collections containing photos with different quality levels and redundancy, among other aspects. This naturally increased the difficulty in selecting or modifying those photos. Within the above context, this survey focuses on systematically reviewing the state-of-art on techniques for the enhancement and analysis of digital photos. Nevertheless, it is not within the scope of this survey to review image quality metrics for evaluating degradation due to compression, digital sensor noise, and affine issues. Assuming the photos have good quality in those aspects, this review is centered on techniques that might be useful to automate the task of selecting photos from large collections or to enhance the visual aspect of imperfect photos by using some perceptual measure.

Character Photo Selection for Mobile Platform

“…Face Features Extraction. In character photos with people as the main subject, the human face is the most attractive area [ 6 ]. The quality of the face has a dominant impact on the quality of the entire photo.…”