Objective Non-Reference Visual Quality Assessment of Image/Videos

Under construction!

Applications of Visual Quality Assessment (VQA):

Categories of VQA:

Fig. 1, Subjective methods by MOS

Objective VQA Metrics

Fig. 2, Vision-based Modeling for VQM

Non Reference VQM

Human Visual System (HVS)

Fig. 3, Campbell and Robson chart

Fig. 4, Spatial CSF

Fig. 5, Velocity CSF

Fig. 6, Spatial-Temporal CSF

Fig. 7, Luminance Adaptation

Cortex Filter [Watson'87]

Fig. 8, Typical cortex transform decomposition in frequency domain

Fig. 9, Cortex Filter from dom filter and fan filter

Fig. 10, Cortex Filter response (right) similar to Gabor function (left) of a cortical receptive field

Fig. 11, DCT Cortex Filter Mapping

Fig. 12, A Simple Threshold Elevation Model

Visual Difference Predictor (VDP) [Daly'93, Bradley'99, Ninassi'08]

Fig. 13, DWT-based subband detection (noise) threshold

Fig. 14, DWT-based subband threshold elevation model

Fig. 15, Spatial frequency dependent DWT (separable) and its rotation to match HVS better.

Fig. 16, DWT-based CSF and rotated DWT-based CSF

Fig. 17, WQA Flowchart

Visual Masking

JND (Just-Noticeable-Distortion) Model

Fig. 18, JND in Psycho Curve

Fig. 19, DCT-based Block Classification

Fig. 20, Block Classification and JND Masking Results

Note: more results are shown in the following webpage.

DVQ (Digital Visual Quality) Model [Watson'02]

Fig. 21, Watson Digital Visual Quality model

Fig. 22, Temporal, spatial and orientation components of DCT threshold model

Visual Attention (Saliency Map) Model

Fig. 23, Context Saliency Results

Note: more results are shown in the following webpage.

Structural Similarity Metric (SSIM) [Zhou'04]

VSNR (Visual SNR) [Chandler'07]

Other Video Quality Metrics

Machine Learning-based Image/Video VQA

3-D Image/Video VQA


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