EI 2006 - San Jose, CA Slide No. 1 Measurement of Ringing Artifacts in JPEG Images* Xiaojun Feng Jan P. Allebach Purdue University - West Lafayette, IN.

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Presentation transcript:

EI San Jose, CA Slide No. 1 Measurement of Ringing Artifacts in JPEG Images* Xiaojun Feng Jan P. Allebach Purdue University - West Lafayette, IN * Research supported by the Hewlett-Packard Company

EI San Jose, CA Slide No. 2 Motivation Applications  Image quality assessment through measuring JPEG artifact perceptibility  Automated workflow for variable data printing Goal  Develop objective no-reference measurement of visual impact for ringing artifacts in JPEG compressed images.

EI San Jose, CA Slide No. 3 Prior Art Full-reference approach – Marziliano et al. (2004)  Usually perfect reference image is not available No-reference approach – Oguz (1999)  Texture of ringing artifacts is not compared with a neighboring smooth region

EI San Jose, CA Slide No. 4 Outline What is ringing artifact Proxy object System detail Sample results Conclusions and future work

EI San Jose, CA Slide No. 5 Overview of ringing artifacts Characteristics of ringing artifact  Ringing artifact is seen to be noise-like variations in the vicinity of major edges.  Activity of the ringing region is higher than that of neighboring smooth region Source of ringing artifact  DCT coefficient quantization

EI San Jose, CA Slide No. 6 Example of ringing artifact JPEG Compressed Image*Enlarged Lighthouse Top * Image source:

EI San Jose, CA Slide No. 7 Ringing artifact measurement Compare the activities of the ringing artifact and the neighboring smooth region Two masking effects are taken into account in the model:  Texture masking  Luminance masking

EI San Jose, CA Slide No. 8 Proxy smooth object Isolated ringing regions need proxy objects with which activities may be compared Proxy object is the smooth object to which ringing region belongs Proxy object can be assigned to ringing region by color similarity Isolated ringing region Proxy object Ringing region with smooth neighborhood

EI San Jose, CA Slide No. 9 Ringing artifact detection Step 1: Detect edges using Sobel operator Step 2: Cluster smooth regions into different object classes according to their color and texture similarity Step 3: Assign a proxy class to each ringing region Step 4: For each edge pixel (x,y), compute a local ringing feature by pooling over the visibility of ringing regions in a local window centered at (x,y) Step 1: Edge detection Step 2: Smooth region clustering Step 3: Ringing proxy assignment Step 4: Local ringing Feature calculation JPEG image Ringing map

EI San Jose, CA Slide No. 10 Smooth region identification Segment an image into  Edges  Potential ringing regions – regions surrounding edges  Smooth regions – regions other than edges and ringing artifact JPEG imageEdge / ringing / smooth segmentation Edge Ringing region Smooth region

EI San Jose, CA Slide No. 11 Smooth region clustering Color clustering Texture clustering Smooth regions Overall clustering Map fusion

EI San Jose, CA Slide No. 12 Region activity calculation The activity of a region is computed based on the luminance changes of neighboring pixels.  - set of neighboring pixel pairs for region  - channel value for pixel

EI San Jose, CA Slide No. 13 Luminance masking Noise perceptibility is affected by background luminance. Noise with very bright or very dark background is not easily detected Chou measured just-noticeable noise levels under various background luminance (1995) We adopt Chou’s model and convert the noisy level threshold into region activity threshold

EI San Jose, CA Slide No. 14 Ringing visibility feature For a ringing region, the overall masking effect is involved as:  − region activity of proxy object (texture masking)  − luminance masking function Ringing visibility feature for region  − size of region  − size of a block (64 for JPEG) Local ringing feature of edge pixel

EI San Jose, CA Slide No. 15 Example of ringing visibility feature JPEG image Activity contrast

EI San Jose, CA Slide No. 16 Sample Result JPEG imageRinging map

EI San Jose, CA Slide No. 17 Sample result Compression ratio increases Quality factor=90 Quality factor=70 Quality factor=50Quality factor=30

EI San Jose, CA Slide No. 18 Conclusion and future work Our ringing artifact measurement  Uses no reference image  Involves both texture masking and luminance masking effects to measure the visual impact of ringing artifact Future work  Conduct psychophysical experiment  Generate a global ringing value from the ringing map

EI San Jose, CA Slide No. 19 Thank you!