Visual Masking Model Implementation for Images & VideoChi Zhang, Yuhong Wang, Sukesh Kaithakapuzha

Department of Electrical Engineering, Stanford University

Motivation Visual Masking Model

Experimental Results

Understanding the image from the human eye’s point of view.

Computational Model of Visual Masking properties of HVS based on pyschophysical data from different research papers on the topic.

Applications of Visual Masking:• Image and Video filtering for display• Video compression• Watermarking• Encryption / Steganography

Image

Higher Importance

Lower Importance

• Just-Noticeable Difference (JND) Model: Eye tracking, spatio-temporal CSF, luminance adaptation, iter-band and intra-band contrast masking, block type classification

• Visual Attention Model: Color contrast, texture contrast, (motion suppression, skin color, face detection, etc)• Weighting Model: Foveation from highest attention points

ApplicationModified

Image

JND Model

Visual Attention Model Weighting Model

ModulationInputVideo

Masking Value

Input Edge ImageBlock Type

ClassificationTexture (B)Edge (W)Plain (G)

JND Visual MaskWith

Visual Attention(Edited)

Related Work•Modeling the Masking Effect of the Human Visual System with Visual Attention ModelAnmin Liu, Maansi Verma and Weisi Lin, Nanyang Technological University, Singapore

•Estimating Just-Noticeable Distortion for VideoYuting Jia, Weisi Lin, Senior Member, IEEE, and Ashraf A. Kassim

•Modeling Visual Attention’s Modulatory Aftereffects onVisual Sensitivity and Quality EvaluationZhongkang Lu, Senior Member, IEEE, Weisi Lin, Senior Member, IEEE,Xiaokang Yang, Senior Member, IEEE, EePing Ong, and Susu Yao.

AcknowledgmentsWe would like to thank Professor Bernd Girod and TA David Chen for their feedback and support for this project.