Last updated on 5 Jan. 2005

Rambler's Top100

The commercial project made for presentation of new algorithm of scaling of raster images. All rights on application of the given algorithm belong to the author of the project.

 
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Resampling

 

Deblurring

 

Dejpeg

 

Denoise

 

Deconvolution

 

Dequantization

 

DJ-M-Spline - the new, linear and best quality algorithm of image cleaning.

JPEG compression breaks an image into rectangular blocks, each representing 8 x 8 pixels of detail, and then independently compresses each block. The result of JPEG compression on a file that was of poor original quality is an ugly, repetitive pattern of blocks. Sometimes the distortions are striking enough to be visible, and those are called artifacts.

 

There are some versions of artifacts:

Blocking artifacts:
Baseline JPEG can only work with 8x8 blocks, one at a time. This causes the best known artifact in compressed images - small square blocks all over the images, known both in JPEG and in video decoders.

Color distortion:
As human eyes are not as sensitive to color as to brightness, much of the detailed color (chrominance) information is disposed, while luminance is retained. This process is called "chroma subsampling", and it means that a color image is split into a brightness image and two color images.

Ringing artifacts:
Both JPEG2000 and JPEG operate in spectral domain, trying to represent the image as a sum of smooth oscillating waves.

Blurring artifacts:
Blurring means that the image is smoother than originally. The pictures were stored at approximately 2.0 bits per pixel, four times weaker compression rate as above.

JPEG Repair - The filter provides improved image quality, removes the so-called 'JPEG artifacts' and improves image clarity. Until recently, there were only three linear methods allowing the clear of image blur, smart blur and noise reduction. The main advantage of these methods is high speed of the realization. However, their application leads to a strong artifacts which, by permanently increasing demands for quality of cleaning, significantly limits the area of their application.

 

Recently, on the market of professional graphic programmes, quite a few more effective and better quality algorithms have appeared. Along with the linear methods non linear (adaptive) algorithms appeared Net Image 5.1, Define, Cleanerzoomer, Jpeg Enhancer, Un Jpeg etc. Notwithstanding the diversity of existing methods of noise and removes of jpeg artifacts, Jpeg Enhancer and Cleanerzoomer are generally recognized as ones of the best quality and the most accurate. However, because none of the said methods does not get an identically good result, the work to create new algorithms is still ongoing with various success.

 

The aim of data spelling appears as the presentation of the new linear method which allows to carry out removes of jpeg artifacts a better quality, better than all known methods, both linear and adaptive. The main advantage of suggested method over the rest of them is the speed (because it appears linear) simpleness of its realization and best quality closest to achievable limits. The method brought to your attention was called Magic spline or M-spline by its author.

Dejpeg-M-spline - algorithm is fully worked out and realized exclusively by the author and all the rights of its use until the decision of sale, belong to the author.

The base of the suggested algorithm (M-spline) lies in application of the new PSN&ER metrics (peak to peak signal to noise and edges ratio) which significantly more accurate (compared with PMS metrics) agrees with the visual valuation of similarity and the new revolutionary approach at working out the algorithm. Valuating the form and size of approximating function, it is also possible to ascertain that obtained algorithms allow getting the quality of the removes of jpeg artifacts which is maximally approximate to the achievable limit from the theory of information point of view. There are also a few algorithm modifications.

In order to confirm above, I suggest to get familiar with practical realization of the algorithm on the well known examples of tasks and solutions.

As the test the following representation has been chosen:

flowers lhouse2

To see the picture click on the fragment

Test - flowers

The resolution of image will be enlarged by 4 times

 

Original Cleanerzoomer Jpeg Enhancer DJ-M-Spline

(New method) enlarged by 2 times
 

Test flowers

Chrominance component

The resolution of image will be enlarged by 4 times

 

Original Jpeg Enhancer DJ-M-Spline

(New method) enlarged by 2 times
 

Test - lhouse

The resolution of image will be enlarged by 4 times
 

Original Cleanerzoomer Jpeg Enhancer DJ-M-Spline

(New method) enlarged by 2 times
 
The real images will be enlarged by 2 times
 

Original DJ-M-Spline

(New method) enlarged by 2 times
 
 
 
Your comments and questions:
vitalybn@fpy.ru
resampling@yandex.ru
vitalybn@yahoo.com

 

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