1. Field of the Invention
The present invention relates to digital still image coding or digital moving image coding, and more particularly to a two-dimensional orthogonal transformation and quantization method and its device.
2. Description of the Related Art
Recently, as a method of digital still image coding and digital moving image coding, a coding method in combination with two techniques of transform coding and quantization is in a widespread use, and there arises a strong demand for a method of realizing the two-dimensional orthogonal transformation and quantization, that is the most important part of the above coding, at a higher speed and with a lower power consumption.
As an example of the still image coding for use on the transform coding and quantization, there is the JPEG standard recommended by JPEG (Joint Photographic Expert Group) of ISO (International Organization for Standardization) and CCITT (Consulting Committee of International Telegraph and Telephone) (at present, ITU-T (International Telecommunication Union-Telecommunication Standardization Sector)).
In the method, an input image is divided into rectangular regions, the two-dimensional orthogonal transformation and quantization is performed on each divided pixel block, and the obtained coefficient block is coded into a bit vector. For the orthogonal transformation, the transformation having the characteristic of resolving into frequency components is used and especially the discrete cosine transformation is often used. Generally, since the adjacent pixels have correlation in an image called a natural image, it is possible to reduce the redundancy of the signal information by concentrating the signal power on a low frequency component, through the orthogonal transformation such as the discrete cosine transformation. Further, by combining the above with the quantization using the man's visual characteristic such that a man is sensitive to a change in the low frequency component but insensitive to a change in the high frequency component, efficient compact coding which can restrain the image deterioration caused by compression becomes possible.
FIG. 2 shows the structure of the still image compact encoder according to this coding method. In FIG. 2, the reference numeral 201 indicates a blocking unit for dividing an input image into the rectangular blocks of predetermined size, the reference numeral 202 indicates a two-dimensional orthogonal transforming unit for performing the two-dimensional orthogonal transformation on each pixel block entered by the blocking unit 201, the reference numeral 203 indicates a quantizing unit for quantizing a transform coefficient supplied from the two-dimensional orthogonal transforming unit 202, and the reference numeral 204 indicates a variable length coding unit for coding the coefficient block supplied from the quantizing unit 203 into a bit vector. The portion surrounded by a dotted line indicates the portion for the two-dimensional orthogonal transformation and quantization processing.
As a typical example of the moving image compact coding using the transform coding and quantization, there are the MPEG-1, MPEG-2, MPEG-4 methods recommended by MPEG (Moving Picture Expert Group) of ISO. These methods perform the inter-frame prediction of predicting an image to be coded based on the prior-frame and the post-frame and the coding in combination with the transform coding of a prediction-error signal. FIG. 3 shows the structure of the moving image compact encoder according to this method. In FIG. 3, the reference numeral 301 indicates a frame scanning unit for replacing input frames in a proper sequence, the reference numeral 302 indicates a blocking unit for dividing a frame entered from the frame scanning unit 301 into rectangular blocks of predetermined size, the reference numeral 303 indicates a frame memory for storing the decoded image of a coded frame as a reference frame for prediction, the reference numeral 304 indicates an inter-frame predicting unit for generating a predicted image by performing an inter-frame prediction according to the input image block signal and the decoded image within the frame memory 303, the reference numeral 305 indicates a prediction-error calculating unit for calculating a prediction error according to the input image block and the predicted image, the reference numeral 306 indicates a two-dimensional orthogonal transforming unit for performing the two-dimensional orthogonal transformation on a prediction error, the reference numeral 307 indicates a quantizing unit for quantizing an orthogonal transform coefficient, the reference numeral 308 indicates a variable length coding unit for coding a quantized coefficient and an inter-frame prediction parameter into a bit vector, the reference numeral 309 indicates an inverse quantizing unit for inverse-quantizing a quantized coefficient, the reference numeral 310 indicates an inverse two-dimensional orthogonal transforming unit for performing an inverse transformation to the two-dimensional orthogonal transformation on an inverse quantized coefficient, and the reference numeral 311 indicates a decoded image calculating unit for calculating a decoded image from the sum of the inverse transformation signal and the predicted image and storing the decoded image into the frame memory 303. The portion surrounded by a dotted line indicates the two-dimensional orthogonal transformation and quantization processing unit.
As mentioned above, the quantization and orthogonal transformation of a two-dimensional image signal plays an important role in both the still image compact coding and the moving image compact coding. However, since the orthogonal transformation and quantization processing generally requires a great deal of multiplication and division calculation, an increase in the processing time and the power consumption owing to the above becomes a big problem. Therefore, there arises a strong demand for a calculation method capable of reducing the calculation amount required for the two-dimensional orthogonal transformation and quantization processing.
The conventional technique for high speed processing by reducing the calculation amount of the two-dimensional orthogonal transformation and quantization introduces a calculation-amount reducing technique especially about the two-dimensional discrete cosine transformation and quantization.
A lot of studies have been performed on the method of calculating the two-dimensional transformation at a high speed, since a long time ago. These studies are classified into the following two types roughly. The first is a method of adopting a high speed method of one-dimensional orthogonal transformation, by returning the two-dimensional orthogonal transformation to the repetition of the one-dimensional orthogonal transformation according to the matrix resolution. The second is a method of reducing the number of the multiplication and division times, without performing the matrix resolution, like the two-dimensional discrete cosine high speed calculation method as disclosed in Japanese Patent Publication Laid-Open (Kokai) No. Heisei 8-335885.
A lot of studies have been performed also on a method of calculating quantization at a high speed. In these days, most often adopted is a method of reducing the number of the burdensome multiplication and division times, by using the characteristic such that a quantization signal of the high frequency component concentrates on zero in compact coding of a natural image, as disclosed in Japanese Patent Publication Laid-Open (Kokai) No. Heisei 03-085871.
However, there is a consistently strong demand for speeding up and saving the power consumption in the two-dimensional orthogonal transformation and quantization processing.
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