LAUSR

The recent advancements in bio-photonics enabled physicians to combine techniques such as narrow-band imaging, fluorescence spectroscopy, optical coherence tomography, with visible spectrum endoscopy video to provide in vivo microscopic tissue characterization in online optical biopsy (Ye et al. 2015 ); (Wang and Van Dam 2004 ). Despite the aforementioned advantages, it is challenging for gastroenterologists to retarget the optical biopsy sites during endoscopic examinations because of the degraded quality of endoscopic video which gets corrupted by haze, noise, oversaturated illumination, etc. Enhancement of video frames by considering color channels independently gives birth to unintended phantom color due to its ignorance of the psycho-visual correspondence. To address the aforementioned, we have proposed a novel algorithm to enhance video with faster performance. The proposed C 2 D 2 A (Cross Color Dominant Deep Autoencoder) uses the strength of (a) bilateral filtering both in spatial neighborhood domain and psycho-visual range; (b) deep autoencoder which learns salient patterns. The domain-based color sparseness has further improved the performance, modulating classical deep autoencoder to color dominant deep autoencoder. The work has shown promise towards not only a generic framework of quality enhancement of video streams but also addressing performance. The current work in turn improves the image and video analytics like segmentation, detection, and tracking the objects or regions of interest.