KR19990066425A - Image Compression and Restoration Method - Google Patents

Abstract

An object of the present invention is to provide a method of compressing and restoring an image that can produce a compressed image with a smaller amount of data when compressing and transmitting a text or still image, and can provide a sufficient image quality for reading an image. In order to achieve the above object, a compression method of an image includes high frequency pass filtering an original image, subsampling the data of the original image by N times, and replacing the subsampled image with a frequency domain. Performing forward forward cosine transform (DCT), quantizing the image transformed into the frequency domain in two dimensions, zig-zag scanning the quantized data into a one-dimensional stream, and And performing variable length coding on the transformed data into a one-dimensional stream, and entropy coding the coded data to output compressed data. The method of restoring a compressed image as described above may include entropy decoding a compressed image, inverse variable length coding (IVLC), and converting the entropy decoded image into one-dimensional data; Inverting and zigzag scanning the one-dimensional data generated through the VLD into two-dimensional data, dequantizing the two-dimensional data, and inverse Discrete Cosine Transform (DCT) And restoring the data output by the inverse DCT by the size of N times.

Description

Image Compression and Restoration Method

The present invention relates to compression and decompression, and more particularly, to a method of compressing and decompressing an image capable of providing a sufficient image quality for making a compressed image with a smaller amount of data and reading the image when compressing and transmitting text or still images. It is about.

Referring to the accompanying drawings, a conventional method of compressing and restoring an image will be described.

Conventional compression and decompression will be described using JPEG as an example.

1A is a block diagram showing a conventional JPEG encoder, FIG. 1B is a block diagram showing a conventional JPEG decoder, and FIG. 2A is a flowchart showing a process of outputting a compressed image using an encoder of a conventional JPEG. 2B is a flowchart showing a process of outputting a reconstructed image using a decoder of a conventional JPEG.

First, a coder for representing a compressed image of a conventional JPEG will be described.

A JPEG encoder for outputting an image input to an 8 × 8 pixel as a compressed image is a forward that converts an image into a frequency domain to remove a low frequency by using the correlation of the image as shown in FIG. 1A. (Forward) A DCT (Discrete Cosine Transform) unit 1, a quantization unit 2 for reducing the amount of data by quantizing the image transformed into the frequency domain by a quantization vector, and a quantization table 2a used for quantization And a zigzag scan processing unit 3 for converting two-dimensionalized data through the quantization unit 2 into a one-dimensional stream and performing zigzag scan, and one-dimensionalized through the zigzag scan processing unit 3. Entropy coding the VLC unit 4 for compressing the data by Variable Length Coding (VLC) and the data coded through the VLC unit 4 in the same manner as Huffman coding. Finally, an entropy coding section 5 for transmitting the compressed data and a code table 5a devised for entropy coding are included.

Next, the JPEG decoder for restoring the compressed image is configured to proceed in the reverse order of the compression process as shown in FIG. 1B. First, an entropy decoding unit 6 for entropy decoding the compressed data, and the entropy decoding. A VLC decoding unit 7 for VLC decoding the decoded data into one-dimensionalized data and an inverse zigzag for reverse-zigzag scanning of the VLC-decoded data into two-dimensionalized data. A scan processor 8, an inverse quantizer 9 for inversely quantizing two-dimensionalized data through the inverse zigzag scan processor 8, and an IDCT unit 10 that is inverse DCT through the inverse quantization. ), A code table 6a for the entropy decoding, and a quantization table 9a used for the dequantization.

A method of outputting a compressed and decompressed image of an image through the encoder and decoder of the JPEG having the above configuration will be described below.

First, the compression method using the encoder of JPEG is a forward discrete cosine transform (FDCT) for converting an image into a frequency domain in order to remove a low frequency by using the correlation of the input image as shown in FIG. 2A. Do Next, the quantized vector is quantized through the quantization table 2a to reduce the amount of data. After the quantized two-dimensional data is dimensionalized by a zigzag scan, it is compressed by Variable Length Coding (VLC), entropy coded like Huffman coding, and finally compressed data is transmitted.

The restoring and outputting of the compressed image is then performed in the reverse order of the compression process as shown in FIG. 2B. First, the compressed data is entropy decoded, reverse VLCed, and then reverse zig-zag-scanned. zag scan to create two-dimensional data and then inverse quantization to inverse Discrete Cosine Transform (DCT) to restore the image.

The conventional compression and decompression method as described above has the following problems.

When the amount of data in the input image is large, the conventional compression method has a limitation in the data transmission bandwidth for compressing and transmitting the amount of data in the input image.

The present invention has been made to solve the above problems, and in particular, an image that can provide a sufficient image quality for making a compressed image with a smaller amount of data when the text or still image is compressed and transmitted, and for reading the image. Its purpose is to provide a method for compressing and restoring a.

Figure 1a is a block diagram showing the encoder of the conventional JPEG

1B is a block diagram showing a conventional JPEG decoder.

2A is a flowchart illustrating a process of outputting a compressed image using an encoder of a conventional JPEG.

2B is a flowchart showing a process of outputting a reconstructed image using a decoder of a conventional JPEG.

3A is a block diagram showing an encoder of the present invention using a standard of JPEG as an embodiment

Fig. 3B is a block diagram showing a decoder of the present invention using a JPEG standard as an embodiment.

4A is a flowchart illustrating a process of outputting a compressed image using an encoder according to an embodiment of the present invention.

4B is a flowchart illustrating a process of outputting a restored image using a decoder according to an embodiment of the present invention.

Explanation of symbols for the main parts of the drawings

21: Enhancer 22: sub-sampling unit

23: FDCT unit 24: quantization unit

24a and 31a: Quantization Table 25: Zig-Zag Scan Processing Unit

26: VLC section 27, 28: entropy coding section

27a, 28a: Code Table 29: VLC Decoding Section

30: reverse zig-zag scan processing unit 31: inverse quantization unit

32: IDCT section 33: interpolator

34: low frequency pass filter

A compression method of an image of the present invention for achieving the above object comprises the steps of high-pass filtering the original image, subsampling to reduce the data of the original image by N times, and the frequency of the sub-sampled image Forward Discrete Cosine Transform (DCT) processing to change to a region, quantizing the image transformed into the frequency domain in two dimensions, and zig-zag scanning the quantized data into a one-dimensional stream. And performing variable length coding to compress the data transformed into the one-dimensional stream, and entropy coding the coded data to output the compressed data.

In addition, the method of restoring an image of the present invention includes entropy decoding a compressed image, inverse variable length coding (IVLC) of the entropy image into one-dimensional data, and the VLD. Reverse zigzag-scanning one-dimensional data into two-dimensional data; inverse quantizing the two-dimensional data; and inverse discrete cosine transform (DCT) on the inverse quantized data; And recovering the data output by DCT by an amount of N times.

Referring to the accompanying drawings, a method of compressing and restoring an image of the present invention will be described.

The present invention is intended to effectively display compressed and reconstructed images, and is particularly suitable for application to text images used in faxes. The present invention can also be used to compress and reconstruct still images. Description of the compression and reconstruction method of the image of the present invention will be described taking the example using JPEG.

Fig. 3A is a block diagram showing the encoder of the present invention using the JPEG standard as an embodiment, and Fig. 3B is a block diagram showing the decoder of the present invention using the JPEG standard as an embodiment. 4A is a flowchart illustrating a process of outputting a compressed image using an encoder according to an embodiment of the present invention, and FIG. 4B is a flowchart illustrating a process of outputting a restored image using a decoder according to an embodiment of the present invention.

In order to compress the input image, the still image or the original image is filtered by an Enhancer, which is a high pass filter, so that the edges of the image are clearer, which is very easy to identify. The present invention is for compressing an input image using such an enhancer (21).

The encoder of the present invention, as shown in Fig. 3A, enhances the edge of the image more clearly by passing only a high frequency of the input image, and half of the compressed data amount ( In order to reduce the above data, the sub-sampling unit 22 which first sub-samples an input image by N: 1 and the sub-sampled image are inputted, and when the sub-sampled image is inputted, A forward DCT (Discrete Cosine Transform) unit 23 for converting an image to a frequency domain to be removed, a quantization unit 24 for reducing the amount of data by quantizing the image converted to the frequency domain with a quantization vector, A quantization table 24a used for quantization, a zigzag scan processing unit 25 for converting two-dimensionalized data through the quantization unit 24 into a one-dimensional stream and performing a zigzag scan, and the zigzag scan The VLC unit 26 for compressing the one-dimensionalized data through the processing unit 25 to Variable Length Coding (VLC) and the data coded through the VLC unit 26 are the same as Huffman coding. The entropy coding unit 27 includes an entropy coding unit 27 for entropy coding and finally transmitting a compressed image, and a code table 27a devised for entropy coding. Here, the subsampling unit 22 serves to remove each pixel in one direction based on a row or a column. The enhancer 21 and the subsampling unit 22 may be configured with a reversed order.

In addition, the decoder according to an embodiment of the present invention for restoring the compressed image is configured to proceed in the reverse order of the compression process as shown in FIG. 3B. First, an entropy decoding unit 28 for entropy decoding the compressed data and the entropy A code table 28a for decoding, a VLC decoding unit 29 for converting the data decoded by the entropy decoding unit 28 into one-dimensionalized data, and reverse-zigzag the VLC decoded data. An inverse zigzag scan processing unit 30 for scanning and converting into two-dimensionalized data, an inverse quantization unit 31 for inverse quantizing two-dimensionalized data through the inverse zigzag scan processing unit 30, and performing inverse quantization A quantization table 31a to be used, an inverse DCT through the inverse quantization, and an IDCT unit 32 for outputting a restored image, and through the IDCT unit 32. Original picture It consists of an interpolator 33 which restores and outputs an image having a data amount to its original size.

At this time, the interpolator 33 is configured to include a low frequency pass filter 34 for filtering the image reconstructed to its original size by low frequency pass filtering.

Next, the interpolator 33 among the components constituting the JPEG decoder of the present invention, for example, is transmitted to the data of 1, 3, 5, 7, ... when compressed, and the interpolator 33 is transmitted. When you restore 2 pixels And 4 pixels By automatically calculating and transmitting the data, it converts the data that has been compressed in half to the data value of the original image.

A compression and decompression method using an encoder and a decoder according to the embodiment of the present invention configured as described above is as follows.

First, the compression method through an encoder according to an embodiment of the present invention filters the edge of an image by filtering the original image such as a still image or a text with a high pass filter to represent only a high frequency with the enhancer 21 as shown in FIG. Becomes clearer and easier to identify. In order to reduce more than half of the amount of data passing through the enhancer 21, first, the input image is subsampled through the N: 1 subsampling unit 22. At this time, when performing 2: 1 subsampling, each pixel is removed in one direction by grasping either the rows or columns of the image as a reference. For example, if you subsample by row, you can create an image with half the original image by removing only even rows, in which case the amount of data Become. In order to remove the low frequency by using the sub-sampled image as described above, a forward discrete cosine transform (FDCT) is performed to convert the image into a frequency domain. Next, the quantized vector is quantized through the quantization table 24a to reduce the amount of data. After the quantized two-dimensional data is one-dimensionalized by a zigzag scan, it is compressed by Variable Length Coding (VLC), and entropy-coded like Huffman coding to finally transmit the compressed image. In this case, the high frequency pass filtering and the N: 1 subsampling of the original image through the enhancer 21 may be performed in reverse order.

Next, a method for restoring the compressed image is as shown in FIG. 4B. First, when the compressed image is input, the compressed data is entropy decoded, reverse VLCed, and then reverse zig-zag scan. After creating two-dimensional data, inverse quantization and inverse discrete cosine transform (DCT) After creating an image with a data amount, it is interpolated and filtered by a low pass filter to restore the image.

In this way, the restoration method can be efficiently compressed and transmitted to transmit a text image such as a fax.

The compression and reconstruction method of the present invention as described above has the following effects.

First, sub-sampling a still picture and a text picture with a characteristic of less image quality deterioration due to subsampling than a moving picture at a 2: 1 ratio can more than double the compression effect. Therefore, there is an advantage in that data can be sufficiently transmitted in a small bandwidth.

Second, the edge of the input image to be compressed in a still image or a text image can be sharpened using an enhancer, thereby providing improved image quality when the image is read.

Claims (6)

High frequency pass filtering the original image; Subsampling to reduce the data of the original image by N times; A forward discrete cosine transform (DCT) process to convert the sub-sampled picture into a frequency domain; Quantizing the image changed in the frequency domain in two dimensions; Zig-zag scanning the quantized data into a one-dimensional stream; Compressing the data transformed into the one-dimensional stream by variable length coding (VLC); And entropy coding the coded data and outputting the compressed data. The image compression method according to claim 1, wherein the edge of the original image is highlighted by high frequency filtering the original image. The method of claim 1, wherein the original image is a text and a still image in the method for outputting compressed data through the above steps. 2. The method of claim 1, wherein the high pass filtering and the subsampling of the original image can be performed in a reversed order. Entropy decoding the compressed image, Converting the entropy decoded image into inverse variable length coding (IVLC) to form one-dimensional data; Reverse-zigzag scanning the one-dimensional data generated through the VLD into two-dimensional data; Dequantizing the two-dimensional data; Inverse Discrete Cosine Transform (DCT) on the dequantized data; And restoring the data output by the inverse DCT by an amount of N times. 6. The method of claim 5, further comprising: restoring the image by filtering the data restored by the size of N times with a low pass filter.