Image analysis – Image compression or coding – Adaptive coding
Reexamination Certificate
1998-07-21
2001-11-06
Couso, Yon J. (Department: 2723)
Image analysis
Image compression or coding
Adaptive coding
C382S251000
Reexamination Certificate
active
06314208
ABSTRACT:
TECHNICAL FIELD
The present invention relates generally to JPEG data compression and more specifically to JPEG data compression for compound images having pictures and text.
BACKGROUND ART
JPEG is the name of both a committee and a standard. JPEG stands for Joint Photographic Experts Group, the original name of the committee that wrote the JPEG standard. The JPEG standard is an international standard which applies to the lossy and lossless compression of either full-color or gray-scale images of natural, real-world scenes.
Lossy image compression compresses by striving to discard as much of the image data as possible without significantly affecting the appearance of the image to the human eye. Lossless compression is compression achieved without discarding any of the image data.
The JPEG standard works well on still photographs, naturalistic artwork, and similar material (which are generally referred to herein as “pictures”), but not so well on lettering, simple cartoons, or line drawings (which are generally referred to herein as “text”). Compound images are those which contain both pictures and text (which are collectively referred to herein as “images”). In some cases, compound images contain pictures which also contain text within the picture itself
This standard is being used in the computer industry. Popular graphics-capable browsers on the World Wide Web can read and write this particular type of image data format, so if a compressed image is sent across the Web to such a browser, it knows how to decompress the image and display it.
Compression is important for two main reasons. The first is storage space. If there will be a large number of images on a hard drive, the hard drive will fill up very quickly unless the data can be greatly compressed. Computers have fixed size buffers and limited memory, and an image has to fit in them otherwise, the image cannot be stored in them.
The second is bandwidth. If data is being sent through a browser or through electronic mail, the more bits that need to be transmitted, the more time is required. For example, with a 28.8K modem it may take half an hour of waiting for a picture to be completely transmitted. If a 50 to 1 compression can be achieved, the same picture can be transmitted completely in about thirty seconds, and if compressed properly, the recipient will not notice the difference between the original and the compressed version.
For full-color images, the uncompressed data is normally 24 bits per pixel. JPEG can typically achieve 10:1 to 20:1 compression on pictures without visible loss, bringing the effective storage requirement down to 1 to 2 bits per pixel. This is due to the fact that small color changes are perceived less accurately than small changes in brightness. Even 30:1 to 50:1 compression is possible with small to moderate defects, while for very low quality purposes such as previews or archive indexes, 100:1 compression is quite feasible.
For gray-scale, and black and white images such large factors of compression are difficult to obtain because the brightness variations in these images are more apparent than the hue variations. A gray-scale JPEG file is generally only about 10%-25% smaller than a full-color JPEG file of similar visual quality with the uncompressed gray-scale data at only 8 bits/pixel, or one-third the size of the color data. The threshold of visible loss is often around 5:1 compression for gray-scale images.
Although there are a number of settings that can be predefined to achieve different compression ratios, there is only one parameter, called the quality factor, that is adjusted regularly in JPEG on an image-by-image basis with one setting for an active image. The quality factor is a single number in an arbitrary, relative scale. A high quality factor will provide a relatively high quality decompressed image, but will require a relatively large file. And, of course the lower the quality, the rougher the approximation of the image and the more compression with a correspondingly smaller file size, but also, the more visible defects, or artifacts, will be in the decompressed final image. Text generally shows significant compression artifacts at higher quality factors than pictures. Further, the quality factor will only give an approximate end file size.
Therefore, a long sought goal in image compression has been to maintain maximum perceptible image quality while achieving maximum compression.
This goal is becoming more difficult to attain because compound documents are just starting to become more and more important. It has only been recently that it has become possible to drop pictures into text documents as much as can be done now. Before, electronic transmissions were either a text document or a picture document. Now, it is more and more common to see a compound image where someone is making a newsletter or setting up a website. People want to drop in some pictures but also want to have text as well. So compound documents are becoming a more important, whether it is just photocopying or just sending to a printer or transmitting across the internet, these have become a more important class of images.
Also, most of the techniques that have been developed in the past for compound documents are based on proprietary (non-standard) compression techniques, so the images could only be decompressed using a specific company's product.
It has long been known that the inability to minimize file size while maintaining high perceptual quality would lead to detrimental compromises in performance so process improvements have been long sought but have eluded those skilled in the art. Similarly, it has long been known that the problems would become more severe with compound documents and thus a generally applicable solution has been long sought.
DISCLOSURE OF THE INVENTION
The present invention provides a simple metric for picture/text segmentation of compound documents in the discrete cosine transform domain. This allows areas of high frequency content such as text to be compressed at a better quality than pictures, thus improving the overall perceptual quality while minimizing the file size. The metric is computed using the quantized output of the discrete cosine transform. No other information is needed from any other part of the JPEG coder.
The present invention provides an image compression system which can be used to apply different, appropriate quantization factors to small blocks of pictures and text to provide significant image compression.
The present invention further provides an image compression system capable of distinguishing between text and pictures in compound images.
The present invention still further provides for preserving the text quality without sacrificing bandwidth while at the same time being JPEG compliant.
The present invention also provides an image compression system which is fully compliant with the latest extensions of the current JPEG standard.
The above and additional advantages of the present invention will become apparent to those skilled in the art from a reading of the following detailed description when taken in conjunction with the accompanying drawings.
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V. Bhasharan, et al: “Text and Image Sharpening of Scanned Images in the J
Konstantinides Konstantinos
Tretter Daniel R.
Couso Yon J.
Hewlett--Packard Company
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