63 citations · 65 across the 14 of their papers we have counts for
11 papers · 1 filter
DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping
Soumendu Majee, Joshua Peter Ebenezer, Abhinau K. Venkataramanan +6
Smartphone cameras have gained immense popularity with the adoption of high-resolution and high-dynamic range imaging. As a result, high-performance camera Image Signal Processors…
GenMFSR: Generative Multi-Frame Image Restoration and Super-Resolution
Harshana Weligampola, Joshua Peter Ebenezer, Weidi Liu +4
Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and en…
Cut-FUNQUE: An Objective Quality Model for Compressed Tone-Mapped High Dynamic Range Videos
Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis +2
High Dynamic Range (HDR) videos have enjoyed a surge in popularity in recent years due to their ability to represent a wider range of contrast and color than Standard Dynamic Range…
Joint Quality Assessment and Example-Guided Image Processing by Disentangling Picture Appearance from Content
Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis +2
The deep learning revolution has strongly impacted low-level image processing tasks such as style/domain transfer, enhancement/restoration, and visual quality assessments. Despite…
Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos
Abhinau K. Venkataramanan, Alan C. Bovik
High Dynamic Range (HDR) videos are able to represent wider ranges of contrasts and colors than Standard Dynamic Range (SDR) videos, giving more vivid experiences. Due to this, HDR…
A FUNQUE Approach to the Quality Assessment of Compressed HDR Videos
Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis +1
Recent years have seen steady growth in the popularity and availability of High Dynamic Range (HDR) content, particularly videos, streamed over the internet. As a result, assessing…
Joint Deep Image Restoration and Unsupervised Quality Assessment
Hakan Emre Gedik, Abhinau K. Venkataramanan, Alan C. Bovik
Deep learning techniques have revolutionized the fields of image restoration and image quality assessment in recent years. While image restoration methods typically utilize synthet…
Quality Modeling Under A Relaxed Natural Scene Statistics Model
Abhinau K. Venkataramanan, Alan C. Bovik
Information-theoretic image quality assessment (IQA) models such as Visual Information Fidelity (VIF) and Spatio-temporal Reduced Reference Entropic Differences (ST-RRED) have enjo…
Edge-Aware Image Color Appearance and Difference Modeling
Abhinau K. Venkataramanan
The perception of color is one of the most important aspects of human vision. From an evolutionary perspective, the accurate perception of color is crucial to distinguishing friend…
One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment
Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis +1
The Visual Multimethod Assessment Fusion (VMAF) algorithm has recently emerged as a state-of-the-art approach to video quality prediction, that now pervades the streaming and socia…
A Hitchhiker's Guide to Structural Similarity
Abhinau K. Venkataramanan, Chengyang Wu, Alan C. Bovik +2
The Structural Similarity (SSIM) Index is a very widely used image/video quality model that continues to play an important role in the perceptual evaluation of compression algorith…