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Compression Artifact Reduction

Problem statement

Low resolution images and videos from digital cameras and cell phones suffer from blocking and ringing artifacts caused by compression. We would like to improve the quality of these images and videos in order to improve their display and printing. Our approach uses weighted combinations of shifted transforms to produce very good results, lowering both ringing and blocking artifacts while adapting automatically to the quality of the input images.

Outline

A fast growing archive of JPEG images and short MPEG video clips is generated by digital still cameras. Unfortunately, ringing and blocking artifacts from the block DCT compression may degrade the quality of these images. Reducing these artifacts may improve the display and printing from cell phone camera photos, video clips, images cropped from high-resolution compressed images and images found on the web. Reducing these artifacts also improves the results from subsequently applied algorithms, such as upsampling and color adjustments, that may otherwise accentuate the compression artifacts. Compression artifact reduction also has the potential to improve the millions of images in the accidental archive that the web has become.

A new method, using weighted combinations of shifted transforms, is developed for deringing and deblocking DCT compressed color images. The method shows substantial deringing improvement over prior methods, maintains comparable deblocking and shows comparable PSNR gains. The method automatically adapts to input image quality, and it may be implemented using low-complexity, swath-based processing. Multiplier-less transforms better suited for parallel hardware implementation are developed. Finally, PSNR comparisons are provided for the different methods. The new method using the DCT transform offers good visual results with PSNR comparable to prior work, and the multiplierless transforms offer good visual results at a slight loss in PSNR.

   View an enlarged example image (original and improved).

Technical details are found here.

Last modified: Wednesday, July 25, 2007 17:47:59 -0700


PhotoPlus: Auxiliary information for printed images

Problem statement

A printed photograph is difficult to reuse because the digital information that generated the print is not available any more. This work describes a mechanism for approximating the original digital image by combining a scan of the printed photograph with small amounts of digital auxiliary information kept together with the print.

Outline

There are three main distortion components introduced by the print-scan channel: 1) registration errors; 2) color distortions; and 3) limitations of the print-scan channel in representing higher frequencies and noise. The auxiliary information that is transmitted comprises three components to correct for these three types of error. It turns out that accurate registration and color-correction can be achieved with very limited auxiliary information. For the example below (the digital image was printed and scanned, and then reconstructed using our algorithm) only 4.6 kilobytes extra information provided a reconstruction of the original with around 32dB PSNR.

However, there is still degradation due to limitations of the print-scan channel as well as residual noise, which is corrected using a Wyner-Ziv layer comprising the bulk of the bit-stream. During reconstruction, the image is first registered and color-corrected with the first two auxiliary information components, and the resultant image then acts as good side-information to decode the Wyner Ziv layer.

scanned image of the print the original digital image registered, color corrected scan using only  4.6 kB

Technical details will be described in the near future (this is joint work with Debargha Mukherjee)


Geometrical methods for lightness adjustment in YCC Color Spaces

Problem statement

The most common color spaces for compressed images and videos are variations of  YCC. We address lightening and darkening images directly in YCC space by developing methods that implement efficient geometrical computations along paths in YCC space. Our approach provides improved results that remove or greatly reduce the color clipping that can occur using traditional methods.

Outline

Lightening or darkening an image is a fundamental adjustment used to improve aesthetics or correct exposure. We developed new geometrical algorithms for lightness adjustment, implementing fast traversal of colors along lightness-saturation curves, applicable when the data starts naturally in YCC space (JPEG images or MPEG videos). Here, YCC refers generically to color spaces with one luminance and two color difference channels, including linear YCC spaces and CIELAB. Our first solution uses a class of curves that allows closed-form computation. Further assuming that saturation is a separable function of luminance and curve parameter simplifies the computations. This approach reduces clipping and better adjusts lightness together with saturation. Preliminary evaluation with 96 images finds good subjective results, and clipping is reduced to about 5% of a prior approach.

View an enlarged example image (original, traditional and improved processing)

Technical details are found here.

Last modified: Wednesday, July 25, 2007 17:47:59 -0700

 


For further information, contact:

ramin (dot) samadani (at) hp (dot) com

 

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