KR20010089765A - Improved cascaded compression method and system for digital video and images - Google Patents

Abstract

A system method for reducing quantization error in a system using a cascade compression scheme is disclosed. The expected quantization error introduced by the cascade compression scheme is determined. The expected quantization error based on the second or higher stage test quantizer is compared. Based on this comparison, a quantizer for the second or higher stage compression is selected to reduce and / or minimize the quantization error caused by the cascade compression scheme.

Description

Improved cascaded compression method and system for digital video and images

Video phones, digital television, teleconferencing, and information highways are just a few of the elements of the modern digital age. Advances in digital image and video processing have helped advance the digital age. In particular, digital image compression methods have played an important role in this development. Image compression reduces the amount of data needed to represent a digital image. For example, color, gray scale, or binary images can be compressed and then decompressed to produce the original image correctly.

In general, compression is performed before storing or transmitting data. This allows a vast amount of information to be stored and / or sent quickly in an economical manner. As is apparent, image compression is a two-way process that usually involves compression and decompression. These processes may not be symmetrical. That is, the time and / or computational power of the compressed process may differ from the others given, depending on the type of algorithm.

In general there are two types of compression: lossy compression and lossless compression. In lossy compression, the decompressed image is similar to the original image but not exactly the same. This is because at least part of the original data has been altered or removed. Lossy compression techniques include sample subsampling, differential pulse coding modulation (DPCM), and quantization of discrete cosine transform (DCT) coefficients. Lossless compression, on the other hand, holds all the data of the original image, which is essentially a fully reversible encoding process. Lossless compression techniques include variable length coding (VLC) and run-length coding (RLC).

The compression ratio is defined as the ratio between the data content to be compressed and the data after compression. The lossy compression method can provide a compression ratio of 100: 1 or more. The lossless compression method generally achieves a ratio of approximately 3: 1. In general, as the loss compression ratio increases, image deterioration increases, so a tradeoff is made.

The compression ratio can be achieved by stage compression or cascaded compression of multiple stages. The image or video source is cascade compressed when the input source signal is compressed in series in multiple stages. For example, in cascading compression, the source signal (image or video) is first compressed to a specific compression ratio and then to a second or higher level to achieve a higher compression ratio. Indeed, higher compression may be required for efficient storage or limited bandwidth transmission.

The Joint Photographic Experts Group (JPEG) and Motion Picture Experts Group (MPEG) standards are the most commonly used compression schemes for images and video, respectively. The JPEG standard is intended for the compression of color or gradation images of natural real-world scenes. Although the JPEG standard includes both lossless and lossy modes, it is usually used in lossy mode to achieve greater compression ratios. Typically, images are transformed into the frequency domain using discrete cosine transform (DCT). As a result, the smaller frequency components are removed and the larger components are left behind. These large value components are then coded with differential pulse code modulation (DPCM) and Huffman coded. JPEG compression has an adjustable feature that allows for a variable compression ratio and allows fine tuning of algorithms for specific application conditions.

The MPEG standard uses the DCT and Huffman coding methods in addition to the interframe coding technology used to provide better compression ratios. MPEG-1 and MPEG-2 are used for low resolution image sequences and high resolution sequences, respectively. MPEG-4 focuses on integrated audio-visual objects and scenes rather than frames. MPEG-7 helps to find audio-visual content.

The compression technique achieves data compression using DCT transform followed by quantization of the DCT coefficients and variable length coding. These compression techniques are lossy compression because they quantize the DCT coefficients. As mentioned above, the lossy compression scheme is that the decompressed data is not an exact duplicate of the original data. For example, in JPEG or MPEG compression, each compression stage in cascaded compression is in fact lossy compression. In addition, performing multiple cascade compression introduces additional loss.

To illustrate this additional loss, reference is made to FIG. 1. 1 shows two lossy compression scenarios (a) and (b). In scenario (a), the source data 10 is compressed by the compression system 11 in a ratio of 20: 1. In scenario (b), source data 10 is first compressed first to 10: 1 and then secondly compressed to 2: 1 by cascade compression system 12. In scenario (b), the second compression stage does not access the original source data 10 but only the compressed signal obtained as the output of the first compression stage. Nevertheless, these scenarios (a) and (b) achieve the same 20: 1 compression. However, the mean square error (MSE) introduced in scenario (b) will always be greater than or equal to scenario (a) due to cascade compression. This additional error is due, in part, to the selection of quantizer values in the second or higher level compression stage.

Some conventional cascade compression systems use a non-degenerative set of quantization factors for continuous compression generation. This set is selected using a numerical relationship such as q value = K * (3 ** n). If one of the quantizers is used in the first generation, one of the other quantizers can be used in the subsequent generation. However, these systems do not provide any insight into how to select quantizers in subsequent generations that will minimize cascading quantization errors. Thus, in this technique, the MSE introduced in cascade compression is minimized, in particular by the second or higher order stages of the cascaded conpression schema, which is lost by the appropriate choice of quantizer. There is a need for improved systems, methods and techniques to minimize this.

Summary of the Invention

It is an object of the present invention to solve the above limitations of the conventional cascade compression system.

It is another object of the present invention to provide a method for calculating the error introduced by cascade compression for a pair of quantizers.

Another object of the present invention is to provide a method for minimizing the losses introduced by cascade compression by selecting the appropriate quantizer.

One preferred embodiment relates to reducing quantization errors introduced in JPEG and MPEG compression schemes.

Aspects of the present invention provide a method of determining an expected quantization error introduced by a cascade compression system of a second or more stage and comparing the expected quantization error of at least two quantizers for the second or more stages. A method for a cascade compression system comprising the steps. The method also includes selecting one of the at least two quantizers according to the comparison result to minimize the quantization error expected for the cascade compression system.

In one preferred embodiment of the present invention, a probability distribution function is used to determine the expected quantization error.

Another aspect of the invention relates to a memory medium and an apparatus for performing the method.

These and other embodiments and aspects of the invention are illustrated in the following detailed description.

FIELD OF THE INVENTION The present invention relates generally to the field of video / image compression, and in particular, the present invention relates to systems and methods for reducing quantization errors introduced in cascade compression of digital video and images.

1 is a schematic diagram of a cascading compression system and a cascading compression system.

2 illustrates a quantizer in a cascaded compression system.

3 illustrates quantization error in a cascade compression system.

4 is a block diagram of a computer system in accordance with an aspect of the present invention.

The additional MSE introduced by cascading compression will now be described with reference to the figure shown in FIG. 2 (a) shows the reconstruction point and the crystal boundary for a uniform quantizer of step size Q ₁ . Reconstruction points are indicated by black spots and the grain boundaries are indicated by short vertical lines. The nth reconstruction point is located at Q ⁿ ₁ (not shown) and the crystal boundaries on either side of Q ⁿ ₁ are located at D ⁿ ₁ and D ^n-1 ₁ (not shown). The crystal boundary lies at approximately midpoint between two consecutive reconstruction points. For a uniform quantizer of step size Q ₁ , the reconstruction point lies at a point that is a multiple of Q ₁ . Any value of the input signal source between the two boundaries is quantized with a reconstruction point that lies between the two boundaries.

Quantizer Q ₁ is used in the first stage (a) of cascade compression, and quantizer Q ₂ is used in the second stage (b) of compression. In the first compression stage, for example, a quantizer Q ₂ is used. In this embodiment, the step size of quantizer Q ₂ is shown to be larger than quantizer Q ₁ . Note that the larger the step size of the quantizer, the more loss is introduced but a higher compression ratio can be achieved. Preferably uniform quantizers such as those used in MPEG I-frame and JPEG compression schemes are used. However, other step sizes and nonuniform quantizers may be used.

In FIG. 2, x represents the value of the input source signal to be quantized. If x is in the range of [Q ⁰ ₂ , D ⁰ ₂ ), this value will be quantized to Q ⁰ ₁ by a single stage quantizer (in this case using only stage b). The "[" symbol indicates that the value is within the range and the ")" symbol indicates that the value is not within the range. In the case of the two-stage quantizer ((a) and (b)), if x is within the range of [0, D ⁰ ₁ ), the output of the first-stage quantizer is Q ⁰ ₁ , and [D ⁰ ₁ , D If it is in the range of ⁰ ₂ ), the output becomes Q ¹ ₁ . The output from stage a is then passed through a second quantizer stage b that quantizes from Q ⁰ ₁ to Q ⁰ ₂ and Q ¹ ₁ to Q ¹ ₂ . Therefore, by cascading compression, the x value in the range [0, D ¹ ₁ ) is quantized to Q ⁰ ₂ and the x value in the range [D ⁰ ₁ , D ¹ ₂ ) to Q ¹ ₂ . The x value in the range [D ⁰ ₁ , D ⁰ ₂ ) is quantized (incorrectly) with a larger mean square error due to the use of cascade compression compared to a single stage quantizer. Likewise, any x values in the range [D ⁰ ₁ , D ⁰ ₂ ) would quantize these values to Q ¹ ₂ if they were single-stage quantizers but would be incorrectly quantized to values of Q ² ₂ by two-stage quantizers. It can be seen that. This additional error is a direct result of cascading compression.

In order to reduce and / or eliminate this additional error, given the quantizers Q ₁ and Q ₂ , the value range of x that is incorrectly quantized must first be determined. In this regard, a specific crystal boundary for the Q ₂ quantizer at D ⁿ ₂ is considered. In such a grain boundaries, one of D ^m greater than ₁ and the other is D ⁿ ₂ 2 of the nearest decision boundary of the small D ^m-1, _one quantizer (Q ₁₎ when the rather is shown in Figures 3a and 3b Is located as.

As an example, consider the following cases.

Case 1 (FIG. 3A):

A single stage Q ₂ quantizer will quantize x to Q ^{n + 1} ₂ . In the two stage quantizers Q ₁ , Q ₂ , the Q ₁ quantizer will quantize x to Q ^m ₁ and the next Q ₂ quantizer will quantize x to Q ⁿ ₁ , thereby introducing additional quantization errors. .

Case 2 (Figure 3b):

A single stage Q ₂ quantizer will quantize x to Q ⁿ ₂ . In the two-stage quantizers Q ₁ and Q ₂ , the Q ₁ quantizer will quantize x to Q ^m ₁ and the next Q ₂ quantizer will quantize x to Q ^{n + 1} ₁ , thereby causing additional quantization error. Is introduced.

In order to identify all ranges of x values to be quantized incorrectly, the calculation must be repeated for all of the boundaries of Q ₂ . However, for a uniform quantizer used in JPEG compression, for example, the calculation only needs to be performed for all the crystal boundaries of Q ₂ in the range of 0 to LCM (Q ₁ , Q ₂ ). LCM (Q ₁ , Q ₂ ) is the least common multiple of two numbers Q ₁ and Q ₂ . The result obtained from this calculation is used to obtain a range of x values that lie outside the range [0, LCM (Q ₁ , Q ₂ )] and incorrectly quantized. As can be seen, the calculation is much simpler in the case of a uniform quantizer.

In each combination of pixel values in the background, the probability distributions of the black pixels and the white pixels may be different. For example, on an all white background, the probability that white pixels are encoded will be much greater than when encoding black pixels. Given the probability distribution f (x) for the input source signal x, the expected quantization error introduced by continuous quantization using quantizers Q ₁ and Q ₂ can be calculated as follows.

The symbol ξ represents a set containing all ranges of x values that are incorrectly quantized as determined above.

The calculation of the quantization error in the above equation is used to select a suitable quantizer in the continuous calculation of the second stage. For example, when quantizer Q ₂ is used in the first stage and there are two possible quantizers Q ₂ , Q ′ ₂ in the second stage, quantization errors can be calculated for these quantizers. . These two possible quantizers are test quantizers. The minimum quantization error value is used to determine the most suitable choice of quantizer, ie Q ₂ or Q ' ₂ ).

Quantizer Q ₂ provides a bit rate r (the larger the rate, the lower the compression) with quantization error E (Q ₂ ) + E (Q ₁ , Q ' ₂ ), and quantizer Q' ₂ quantizes If it is expected to provide a bit rate r 'with error E (Q' ₂ ) + E (Q ₁ , Q ' ₂ ), the ratio of rate to quantization error can be used as a measure in the selection of the quantizer. Where E (Q ₂ ) and E (Q ' ₂ ) are quantization errors inherently generated by the quantizer and are independent of the additional errors caused by cascade compression.

Of course, quantizers other than Q ₂ or Q ′ ₂ described above may also be used as starting points. The choice of quantizer is based in part on the overall compression ratio desired. In addition, some trial and error may be used in selecting an initial quantizer. The quantization error for several quantizers can be calculated as described above, so the most suitable quantizer is selected.

As mentioned above, one embodiment of the present invention relates to an application using JPEG and MPEG compression. These compression methods spatially partition the input source data into 8 x 8 contiguous blocks that are DCT transformed into 64 DCT coefficients. This is followed by the quantization of the DCT coefficients. DC coefficients are differentially coded. The 63 remaining AC coefficients are encoded by specifying the continuous-length of the zero coefficients and then encoding the next non-zero coefficient values.

In the case of JPEG, the entries in the quantization table determine the quantization used for the different DCT coefficients. Different quantization tables can be used for different bands (e.g., luminance and chrominance), but for a single band the quantization table is fixed. In order to apply the quantization selection method of the present invention to recompressing already compressed JPEG data, the probability distribution f (x) for each DCT coefficient must be known. Experimentally it is known that the distribution of AC DCT coefficients follows the Laplacian distribution. Note that the distributions associated with the Laplacian distribution are different for different DCT coefficients. This parameter can be estimated or other distributions such as Rayleigh or Gaussian can be obtained from the compressed data.

It will be appreciated that the Laplacian distribution can be used for both the DCT coded image and the luminance and chrominance channels of the MPEG error term. MPEG compression uses DCT to encode error terms as well as picture information. The error term is obtained from the MPEG motion compensation algorithm. The error term is obtained by subtracting an image block from a block on another picture in the sequence and applying a DCT to the difference. Accordingly, a picture can be hatched using a few bits if there are only a few changes in the image.

In addition, in the MPEG case, the preferred embodiment focuses on I- (intra-encoded) frames in the MPEG format. An I-frame consists of only intrablocks without referring to other pictures. These frames can act as random access points in the sequence. Other MPEG frame types may also be used, such as P- (predictive encoding) and B- (bidirectional interpolation) frames.

For example, for each (I) frame in MPEG video, the quantizer value is determined by quantizer_scale and quantization table. Different quantization tables can be used for chrominance and luminance. The quantization table is fixed for each frame, but the quantizer_scale may be changed for each macroblock. In one embodiment, the quantizer scale is selected for each MPEG frame macroblock using the quantum selection method described above. However, note that the quantizer_scale cannot be changed for each DCT coefficient. This value is fixed for the entire macroblock. Since the human visual system is more sensitive to quantization errors of low frequency coefficients, quantization_scale is preferably selected to minimize the average quantization error of the selected low frequency coefficients.

4 illustrates a video / image processing system 20 in which the present invention may be implemented. By way of example, system 20 may be a video / image storage device such as a television, set top box, desktop, laptop or palmtop computer, personal digital assistant (PDA), video cassette recorder (VCR), digital video recorder (DVR), TiVO device, or the like. , And some or a combination thereof and other devices. System 20 includes one or more video / image sources 22, one or more input / output devices 24, a processor 25, and a memory 26. The video / image source 22 may refer to, for example, a television receiver, a VCR or other video / image storage device. Alternatively, the source 22 may be, for example, the Internet, wide area network, metropolitan area network, local area network, terrestrial broadcasting system, cable network, satellite network, wireless network, or telephone network, and some or combinations thereof and other network types, etc. It may refer to one or more network connections that receive video / images from a server or servers through a global computer communication network.

The input / output device 24, the processor 25 and the memory 26 communicate via a communication medium 27. Communication medium 27 may refer to a bus, a communication network, one or more internal connections of circuits, circuit cards or other devices, and portions and combinations thereof and other communication media. The input video / image from the source 22 is processed according to one or more software programs stored in the memory 26 and executed by the processor 25, thereby outputting the output video to a display device 28 such as a television display, a computer monitor, or the like. Generates an image.

In a preferred embodiment, the calculation of the expected quantization error due to cascade compression and the selection of a suitable quantizer is implemented in computer readable code executed by the system 20. The code may be stored in memory 26 and / or may be read / downloaded from a memory medium such as a CD-ROM or floppy disk. In other embodiments, hardware circuitry may be used in place of or in combination with software instructions that implement the invention.

It should be noted that the specific configuration of the system 20 as shown in FIG. 4 is merely an example. Those skilled in the art will appreciate that the present invention can be implemented using a wide variety of alternative system configurations.

Although the present invention has been described in terms of specific embodiments, it should be understood that the present invention is not intended to be limited or limited to the embodiments disclosed herein. For example, the present invention is not limited to any specific method of compression, frame type or probability distribution. On the contrary, the invention is intended to cover various modifications and variations that fall within the spirit and scope of the appended claims.

Claims (17)

In the method for the cascade compression system 12, Determining an expected quantization error introduced by the second or higher stage cascade compression system; Comparing expected quantization error of at least two quantizers for the second or higher stage; And Selecting one of the at least two quantizers according to the comparison result. The method of claim 1, Wherein the expected quantization error is determined using a probability distribution function. The method of claim 2, And the probability distribution function is a Laplacian distribution. The method of claim 2, The selecting step selects one quantizer in accordance with a ratio of an expected bit rate and an expected quantization error. The method of claim 2, The probability distribution function is determined according to the input data (10) to be compressed. The method of claim 1, Wherein the at least two quantizers are determined according to a required compression ratio of the cascade compression system. The method of claim 1, Wherein the cascading compression system comprises at least one of a JPEG or MPEG system. The method of claim 1, The determining step includes determining a set of ranges for values of input data to be incorrectly quantized by the cascade compression system. A memory medium comprising code for a cascade compression system 12, The code is Decision code for calculating an expected quantization error introduced by the second or higher stage cascade compression system; Comparison code for comparing an expected quantization error of at least two quantizers for the second or higher stage; And a selection code allowing selection of one of at least two quantizers in accordance with a result of the comparison code. The method of claim 9, And the expected quantization error is determined using a probability distribution function. The method of claim 9, And the probability distribution function is a Laplacian distribution. The method of claim 9, The cascaded compression system comprises at least one of a JPEG or MPEG system. In the cascade compression apparatus 20, A memory 26 that stores executable code; And (i) determine the expected quantization error introduced by the secondary or higher stage cascade compression system, and (ii) compare the expected quantization error of at least two quantizers for the second or higher stage. And (iii) a processor 25 for executing code stored in the memory 26 to enable selection of at least two quantizers according to a comparison result. ). The method of claim 13, And the expected quantization error is determined using a probability distribution function. The method of claim 14, And the probability distribution function is a Laplacian distribution. The method of claim 13, The cascade compression system (12) comprises at least one of a JPEG or MPEG system. In cascading compression system 12, Means (25, 26) for determining an expected quantization error introduced by the cascade compression system; Means (25, 26) for comparing expected quantization errors based on possible quantizers for a second or higher stage of the cascade compression system; And Means (25, 26) for selecting one of the possible quantizers to reduce the expected quantization error.