Image analysis – Image compression or coding – Transform coding
Reexamination Certificate
1999-08-31
2002-03-05
Boudreau, Leo (Department: 2621)
Image analysis
Image compression or coding
Transform coding
C382S251000, C375S240030, C375S240200
Reexamination Certificate
active
06353685
ABSTRACT:
FIELD
The present invention relates to a method and apparatus for image compression. In particular, the invention provides an image compression technique that is faster and more efficient than conventional image compression techniques.
BACKGROUND
Visual communications is no longer thought about in terms of when, if, or will be. The need, and the underlying technologies are there—now. What's been missing is the availability of digital video at the best quality and performance possible, at a cost that isn't prohibitive. The digital video camera is becoming the next great input device for the PC. And the only way to get high quality video images into PC is through a camera. However, due to the large bandwidth requirement to transmit huge amount of video data, engineers are scrambling to determine feasible solutions.
A conventional solution is using an external capture card coupled to a camera. The camera transmits every frame of video data back to the capture card via regular cable. To install the system, the users have to remove a computer housing, plug in the cards, and potentially solve the hardware/software conflicts to have a working system. Though this solution can support full frame-rate, full-color depth, it is somewhat an expensive solution.
Another solution is Image compression, which is a beneficial technique for reducing the size of data that defines an image. Conventional image compression techniques are well known in the art and include JPEG (directed at still images) and MPEG (directed at moving images). While the JPEG standard is directed at still images, it can be applied to moving images so long as the images are communicated on a frame-by-frame basis. The MPEG standard utilizes sophisticated movement analysis that provides high compression, but also requires significant processing capabilities.
Conventional JPEG image compression takes regions of an image (typically an 8×8 group of pixels) and characterizes each region as a block. The technique then converts the block from the time domain to the frequency domain using a discrete cosine transform (DCT). The data is then quantized and entropy encoded. JPEG can reduce image data significantly (by 50-90%) depending on the image. However, JPEG requires a fair amount of processing capability in order to process the data. Accordingly, one of the limitations of conventional JPEG is that it has a block size fixed at 8×8 and requires a fair amount of processing to compress and decompress the image.
A goal of the invention is to overcome the identified limitations and provide an image compression technique that is both fast and efficient. Additionally, a goal of the invention is to provide a fast and efficient image compression technique that can be applied to moving images.
SUMMARY
The invention overcomes the identified problems and provides an image compression technique that is both fast and efficient. Additionally, the invention provides a fast and efficient image compression technique that can be applied to moving images. The invention is sometimes referred to herein as JPEG-Lite. An exemplary embodiment of an image compression apparatus for compressing image data provided to an input terminal and providing compressed data to an output terminal includes a 4×4 weighted digital cosine transformer (DCT) coupled to the input terminal and configured to convert the image data into weighted frequency data. A zigzag circuit is coupled to the DCT and configured to zigzag process the frequency data and generate create zigzag data. A Q-factor estimator is coupled to the DCT and configured to estimate the frequency data and generate a Q-factor. A DC coding circuit is coupled to the zigzag circuit and configured to code the zigzag data and generate a DC code. A quantization circuit is coupled to the zigzag circuit and the Q-factor estimator and configured to quantize the zigzag data based on the Q-factor and generate quantized data. A run-length coding circuit is coupled to the DC coding circuit and the quantization circuit and configured to encode the quantized data to create variable length data as the compressed data to the output terminal. In this manner, the original image is compressed.
In one aspect of the invention, the invention divides the 4×4 weighted DCT into a two-dimensional DCT for processing. In another aspect of the invention, the two-dimensional DCT is further divided into a one-dimensional DCT for processing. In these aspects of the invention a special coefficient table is employed to gain a high degree of compression. A quantization table is selected to provide high compression while retaining a significant amount of reproducibility of the original image. A DC coder is also selected to improve compression. Run Length Coding (RLC) and variable length coding (VLC) can also be employed to improve compression.
One embodiment of the invention provides that when bandwidth is limited between the image capturing device (e.g. camera) and the storing device (e.g. computer) or reproducing device (e.g. monitor), a dynamic bit rate controller is invoked to reduce the bandwidth while maintaining a high quality image. Another embodiment of the invention provides error detection so that the receiving device can identify errors and take steps to prevent the errors from corrupting the entire image. Additionally, while the invention is described with reference to specific hardware, the invention can also be implemented in software employing the functions as described herein.
Advantages of the present invention include an image compression technique that is both fast and efficient. Additionally, the invention provides a fast and efficient image compression technique that can be applied to moving images.
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Wallace G.K, JPEG still picture compression standard, consumer electronics, IEEE vol. 38 xviii-xxxiv, Feb. 1992.
Chen Chia-Hung
Chu Der-Ren
Kao Sophia Wei-Chun
Lee Wei-Chun
Wang Kang-Huai
Boudreau Leo
Divio, Inc.
Flehr Hohbach Test Albritton & Herbert LLP
Sherali Ishrat
LandOfFree
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