Television – Bandwidth reduction system – Data rate reduction
Reexamination Certificate
1996-12-18
2002-09-24
Britton, Howard W. (Department: 2713)
Television
Bandwidth reduction system
Data rate reduction
C348S407100, C348S607000, C348S699000
Reexamination Certificate
active
06456328
ABSTRACT:
1. Field of the Invention
The present invention relates to a low bit-rate communication system for multimedia applications, such as a video teleconferencing system, and more particularly, to a method of, and system for, filtering video images prior to video coding.
2. Description of the Related Art
The storage and transmission of full-color, full-motion images is increasingly in demand. These images are used not only for entertainment, as in motion picture or television productions, but also for analytical and diagnostic tasks such as engineering analysis and medical imaging.
There are several advantages to providing these images in digital form. For example, digital images are more susceptible to enhancement and manipulation. Also, digital video images can be regenerated accurately over several generations with only minimal signal degradation.
On the other hand, digital video requires significant memory capacity for storage and equivalently, it requires a high-bandwidth channel for transmission. For example, a single 512 by 512 pixel gray-scale image with 256 gray levels requires more than 256,000 bytes of storage. A full color image requires nearly 800,000 bytes. Natural-looking motion requires that images be updated at least 30 times per second. A transmission channel for natural-looking full color moving images must therefore accommodate approximately 190 million bits per second. However, modem digital communication applications, including videophones, set-top-boxes for video-on-demand, and video teleconferencing systems have transmission channels with bandwidth limitations, so that the number of bits available for transmitting video image information is less than 190 million bits per second.
As a result, a number of image compression techniques such as, for example, discrete cosine transformation (DCT) have been used to reduce the information capacity (bytes) required for the storage and transmission of digital video signals. These techniques generally take advantage of the considerable redundancy in the image information for any natural image, so as to reduce the amount of information used to transmit, record, and reproduce the digital video images. For example, when an object in a video sequence has many pixels that are identical, the discrete cosine transformation (DCT) technique uses zero data components to identify such redundant pixels, so as to eliminate the image information (bytes) that is associated with such pixels from being compressed and transmitted. In contrast, the discrete cosine transformation technique uses non-zero data components to identify pixels that are not identical. Thus, if the video image to be transmitted is an image of the sky on a clear day, the discrete cosine transform (DCT) image data information has many zero data components, since there is little or no variation in the objects depicted for such an image. As a result, the image information of the sky on a clear day is compressed by transmitting only the small number of non-zero data components used to identify pixels that are not identical.
One problem associated with image compression techniques, such as discrete cosine transformation (DCT) is that for low bitrate applications, DCT techniques tend to produce decoded images disturbed by errors. One type of commonly occurring error is referred to as “mosquito noise”, since its appearance in a decoded video segment gives the illusion of “mosquitoes” closely surrounding an object. “Mosquito noise” is typically present at the edges and contours of objects in a video sequence. Noise, such as “mosquito noise”, occurs when there is too much image information to be coded in the video sequences, than there are bits available for transmission. For example, the DCT data information for edges and contours of objects depicted in a video sequence have many non-zero data components, since such areas contain few redundancies across the image. If the number of non-zero data components for the edges and contours of an object is larger than the number of bits available for transmission, such as, for example, with low bitrate telephony systems, some of the data components for the object are not coded accurately. As a result, some of the inaccurately coded data components get translated into images containing “mosquito noise”, when the transmitted data components are decoded.
Typically, video image errors such as “mosquito noise”, are reduced with the use of a prefilter which filters the video signal prior to image compression. The prefilter is characterized with a defined range of frequencies. When a video signal is input to the prefilter, only those frequencies contained in the video signal that are within the range of defined frequencies for the prefilter, are output to a video coder. The frequencies contained in the video signal that are outside the range of defined frequencies for the prefilter are suppressed. Thus, prefiltering essentially eliminates some of the image information from the video sequences, allowing the sequences to be coded using fewer bits, so as to reduce coding errors, such as, “mosquito noise”.
Unfortunately, since the prefilter filters the video signal using a single, fixed range of frequencies, image information is uniformly eliminated from areas deemed important to the content of the video sequence as well as from areas that are deemed unimportant. For example, when a video sequence containing facial areas is prefiltered using a single, fixed range of frequencies, those frequencies of the facial areas that are outside of the range of defined frequencies for the prefilter, are suppressed. As a result, facial areas are often depicted with overly smoothed out features, giving the faces an artificial quality, since fine features such as wrinkles that are present on faces found in the original video sequence tend to be filtered out. Image areas of a video sequence that are typically deemed important include edges of objects, skin areas, facial regions and areas surrounding a moving object. Image areas of a video sequence that are deemed less important include the background of the image. Although, prefiltering of the video signal reduces the errors attributable to: coding, the use of a fixed range of filtering frequencies defines a single strength filter, which automatically eliminates image information from some important areas of the video sequence, resulting in an overall loss of picture quality when the original image is compared to a decoded version of the same image.
Accordingly, prefiltering arrangements that reduce the number of bits to be coded using image compression techniques continue to be sought.
SUMMARY OF THE INVENTION
The present invention is directed to an object-oriented filter for filtering video images prior to video coding and, in an illustrative application, is used in conjunction with the video coder of video encoding/decoding (Codec) equipment. The object-oriented filter initially analyzes an input video signal to map the location of picture elements (pixels) that are associated with one or more image parameters contained in the video sequences. The term image parameter as used herein refers to a parameter that is associated with a certain aspect of the video sequence. Examples of image parameters include the edges of objects, skin areas, eyes-nose-mouth (ENM) regions, and the areas surrounding moving objects.
Once the pixels associated with one or more of the image parameters are mapped, the object-oriented filter selects a filtering factor for each identified image parameter of the video sequence. The filtering factor adjusts the strength of the filter that subsequently filters those pixels associated with each identified image parameter. Thus, in a single frame of a video sequence the pixels associated with one or more image parameters are first mapped and then filtered by the object-oriented filter of the present invention using several differing filter strengths in contrast to the single filter strength utilized by filters of the prior art to filter all pixels of a video sequence.
The filtering factors
Britton Howard W.
Lucent Technologies - Inc.
Verlangieri Patricia A
LandOfFree
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