WO1999012356A1 - Procede pour comprimer des informations image - Google Patents

Procede pour comprimer des informations image Download PDF

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Publication number
WO1999012356A1
WO1999012356A1 PCT/DE1998/002249 DE9802249W WO9912356A1 WO 1999012356 A1 WO1999012356 A1 WO 1999012356A1 DE 9802249 W DE9802249 W DE 9802249W WO 9912356 A1 WO9912356 A1 WO 9912356A1
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WO
WIPO (PCT)
Prior art keywords
image
image information
movement
degree
current image
Prior art date
Application number
PCT/DE1998/002249
Other languages
German (de)
English (en)
Inventor
Gerhard Bock
Stefan Meister
Original Assignee
Siemens Aktiengesellschaft
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Aktiengesellschaft filed Critical Siemens Aktiengesellschaft
Publication of WO1999012356A1 publication Critical patent/WO1999012356A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/59—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving spatial sub-sampling or interpolation, e.g. alteration of picture size or resolution
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H04N19/126—Details of normalisation or weighting functions, e.g. normalisation matrices or variable uniform quantisers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H04N19/137—Motion inside a coding unit, e.g. average field, frame or block difference
    • H04N19/139—Analysis of motion vectors, e.g. their magnitude, direction, variance or reliability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/80—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation

Definitions

  • the present invention relates to a method for compressing image information according to the preamble of claim 1.
  • the present invention relates to a method for compressing image information according to the preamble of claim 1, as is used in image recording systems, in particular in mobile video telephones.
  • image or video data or information is compressed and encoded before it is transmitted to a receiver in order to reduce the amount of data to be transmitted and to increase the transmission security.
  • the compression and encoding rate can be set independently of the amount of data to be processed.
  • compression and coding systems are also known in which the compression and coding rate depends on the complexity of the image to be processed and the movement within the image, i.e. the movement of the source data varies in order to ensure a constant quality of the received overall picture.
  • a higher compression and coding rate can be selected for processing a complex picture, while the compression and coding of a simple picture is carried out with a lower compression and coding rate, so that a constant quality for the transmitted overall picture is ensured.
  • picture signals have the property of being predictable within certain limits. This means that prediction of the next picture is possible on the basis of previous pictures. In order to predict the next image or the image information corresponding to the next image, a so-called. Motion estimation performed, due to a the next image is predicted in a motion detected motion.
  • FIG. 2 shows a simplified block diagram to explain the mode of operation of the MPEG2 algorithm.
  • Certain image information or image data i is present on the input side and has been recorded or generated, for example, by a camera, a CCD image sensor or another image recording device.
  • This image information i is fed to an image information memory 1, which stores the image information i in frames, ie in a sequence of frames.
  • the data of the image information memory 1 are fed to a DCT transformation device 3 which subjects the picture information to a discrete cosine transformation, the output signals of the DCT transformation device 3 being fed to a quantization device 4 which determines the quantization stages or signals present at their input. Assigned quantization intervals and in this way reduces the bit stream to be processed and transmitted and realizes the actual compression.
  • the output signals of the quantization device 4 are fed to a coding device 5 which encodes the signals according to a predetermined coding scheme and outputs them for transmission to a receiver.
  • the output signals of the quantization device 4 are also fed to an inverse quantization device 6 and an inverse DCT transformation device 7, so that the data or signals present at the input of the DCT transformation device 3 appear again at the output of the inverse DCT transformation device 7 .
  • the original image data or image information is thus stored in a (full) image memory 8.
  • a motion estimation or movement detection device 9 is provided which, on the basis of the image information stored in the image memory 8 and the image information present at the input of the compression and coding system i, a movement between the previous image stored in the image memory 8 and that at the output of the Image information memory 1 occurring or current image detected.
  • the motion estimation device 9 When a movement is detected between the stored previous image and the current image occurring on the input side, the motion estimation device 9 generates an image vector v which represents the movement between the stored previous image and the current image applied on the input side.
  • the motion estimation device 9 transmits the motion vector information v to a motion compensation device 10 which, depending on the motion vector v thus transmitted and the likewise transmitted image information of the previous image, which is stored in the image memory 8, is a prediction for the next, that is to say the currently applied, image carries out.
  • the motion compensation device 10 determines image information i 'which represents an estimate or prediction for the image currently present on the input side, this predicted image information being fed to an adder 2 which supplies the predicted image information i' of the motion compensation tion device 10 compares with the actual image information i of the current image and generates a corresponding difference signal ⁇ i.
  • This difference signal ⁇ i, ie the difference between the predicted image information i 'and the actual image information i is known as the so-called.
  • “Prediction error” denotes, with only the prediction error ⁇ i being transformed, quantized and coded using the devices 3, 4 and 5.
  • the instantaneous image can be used to draw conclusions about the instantaneous image based on the received prediction error ⁇ i on the basis of the previously received image information of the previous image
  • This method of motion estimation has the advantage that the signals can be transmitted at a higher bit rate, since the bandwidth of the transmitted difference signal ⁇ i is smaller than the bandwidth of a normal quantized signal, due to the feedback loop with the motion estimation device 9 and the motion compensation device 10 quantization errors of the quantization device 4 cannot accumulate.
  • This MPEG2 algorithm described above is generally used for compressing and encoding image information or image data.
  • the MPEG2 algorithm can also be used in mobile imaging systems, such as video cameras or mobile video telephones.
  • the H.261 or H.263 algorithm is mainly used.
  • Such mobile image recording systems are used to transmit a wide variety of image contents. Images or scenes with a lot of movement require a high refresh rate. Since the human eye can detect and capture blurring of the image less accurately with images with a lot of or fast movement, images with a lot of movement can be transmitted with a lower image sharpness, so that a data rate reduction is possible in this way. In contrast, when the images are calm, the human eye expects high image sharpness, so that in this case the image rate can be reduced while the image has to be transmitted with a high image sharpness.
  • the invention is therefore based on the object of proposing an improved method for compressing image information, with the aid of which an optimal image sharpness of the images to be processed is always guaranteed and the greatest possible reduction in the amount of data to be processed is ensured.
  • this method for compressing image information should also be able to be implemented in a simple manner and as cheaply as possible in mobile video telephones.
  • the method according to the invention can be applied to any method or device that works according to an algorithm described above with motion estimation. works, e.g. the H.261, H.263, MPEG1, MPEG2 or MPGEG4 algorithm.
  • the motion vector generated as a result of the motion estimation is analyzed and from this, for example by means of statistical evaluation, it is assessed whether an image or a scene with a lot or little motion or with fast or slow motion is present. Depending on this assessment, a decision is made as to whether it is necessary to work with a high or low image sharpness, and certain parameters which influence the image sharpness are then set accordingly.
  • images with a lot of movement or with fast movements with a lower sharpness are processed, while images with little movement or with slow movements are processed with a higher sharpness.
  • an automatic setting of the refresh rate i.e. the temporal image resolution, so that after recognizing an image with a lot of movement or with fast movements, the corresponding image information with a higher temporal resolution, i.e. with a higher refresh rate than an image with little movement or slow movements. This accommodates the natural human sense of vision and improves the subjectively perceived quality.
  • the image sharpness is adjusted by changing the quantization parameter, that is to say by appropriately adapting the number of quantization intervals.
  • the image information that actually corresponds to a current image can be pre-filtered, with certain filter elements depending on the movement detected in the current image. Parameters of the corresponding filter algorithm or the corresponding prefilter can be adapted.
  • the method according to the invention is basically applicable to all methods and devices in which an algorithm with motion estimation is used.
  • the automatic setting of the desired image sharpness is achieved according to the invention simply by intervening in the corresponding algorithm, so that there is always the best possible reduction in the data to be processed with an optimal image quality.
  • the process according to the invention is particularly easy, e.g. as a software extension in mobile video telephones without extensive circuit changes being necessary.
  • the method according to the invention can also be used in any other mobile image recording system, such as e.g. can also be used in camcorders or video cameras.
  • the method according to the invention is not tied to use in a mobile image recording system, but can also be used in stationary image recording systems.
  • Fig. 1 shows a simplified block diagram for
  • FIG. 2 shows a simplified block diagram for explaining a known method for compressing and encoding image information with the aid of a motion estimation.
  • the invention is described in more detail below with reference to FIG. 1 using a preferred exemplary embodiment, according to this embodiment, the so-called. MPEG2 algorithm is used to compress image information.
  • MPEG2 algorithm is used to compress image information.
  • the method according to the invention can in principle be applied to any algorithm with motion estimation, in particular also to the H.261 or H.263 algorithm.
  • Fig. 1 shows a united eight block diagram of an arrangement for performing the method according to the invention according to the preferred embodiment.
  • the basic structure of the block diagram shown in FIG. 1 essentially corresponds to the block diagram shown in FIG. 3.
  • the sequential image information of a corresponding image recording device e.g. of any image sensor or a video camera etc. are stored in an image information memory 1, the image information being combined into frames or full images.
  • image information i is read out for each full image.
  • image information to be transmitted is subjected to a discrete cosine transformation (DCT) by a DCT transformation device 3.
  • the discrete cosine transformation is an orthogonal transformation and maps the discrete temporal samples of the image information into discrete values of the frequency domain.
  • the output signal of the DCT transformation device 3 is fed to a quantization device 4.
  • the quantization device 4 quantizes the transformation result of the DCT transformation device 3 with a specific quantization value or a specific quantization rate, the entire value range of the transformation result being subdivided into a specific number of quantization intervals and the value of the transformation result result is assigned to a specific quantization interval. In this way, the quantization device 4 reduces the amount of bits to be processed and transmitted and thus carries out the desired compression with a corresponding quantization value.
  • the sampling values of the transformation result can be assigned to the individual quantization intervals according to a linear or non-linear characteristic.
  • certain sample values of the image information signal can be quantized more precisely than with a linear quantization, which is particularly advantageous if these values occur more frequently or errors in these values are more conspicuous or of greater importance.
  • certain parameters of the quantization device 4 are variable and adjustable, such as, in particular, the number of quantization intervals or also the characteristic curve relevant for the assignment of the samples of the transformation result to the individual quantization intervals.
  • the output signal of the quantization device 4 is fed to a coding device 5, which finally subjects the quantized transformation result to a specific coding and outputs the quantized and coded image information signal for transmission.
  • the coding device 5 can, for example, carry out a run-length limited (RLL) coding.
  • the output signal of the quantization device 4 is also fed to an inverse quantization device 6 and an inverse DCT transformation device 7, the inverse quantization device 6 quantizing the quantization device 4 and the inverse DCT transformation device 7 DCT transformation of the DCT transformation device 3 reverses, so that at the output the inverse DCT transformation device 7 again the original input data of the DCT transformation device 3 occur.
  • the image information supplied by the inverse DCT transformation device 7 is stored in an image memory 8, the image memory 8 storing in particular the image information frame by frame or frame by frame.
  • an interpolation device 11 is also provided, which preferably reads out the image information stored in the image memory 8 frame by frame and by interpolation between two adjacent pixels (pixels) and obtains additional image information which is between the correspond to two pixels. In this way, the interpolation device 11 can double the image resolution.
  • the interpolation device 11 stores the image information obtained as a result of the interpolation with the increased resolution.
  • a motion estimation device 9 receives, on the one hand, the image information i of a current or current image appearing at the output of the image information memory 1, and via the interpolation device 11, the data in the
  • Image memory 8 stored image information of the previous image. By comparing these two pieces of image information, the motion estimation device 9 can recognize a movement in the current image compared to the previous image and, based on the image information of the previous image stored in the image memory 8, determines a motion vector v which represents the displacement of the current image compared to the previous image represents.
  • This motion vector v is fed to a motion compensation device 10 which, as already explained with reference to FIG. has been elucidated - makes a prediction for the image information of the currently present image on the basis of the motion vector v and also the image information of the previously stored previous image also supplied to it.
  • the motion compensation device 10 thus executes a motion compensation prediction and outputs image information i ′ which correspond to the image predicted by the motion compensation device 10.
  • the image predicted by the motion compensation device 10 should correspond to the image currently present on the input side, ie the image information i 'should correspond to the image information i of the current image.
  • the prediction of the motion compensation device 10 is compared in an adder with the actually applied image, ie the adder forms the difference between the image information i that actually corresponds to the current image and the image information i ′ of the current image predicted by the motion compensation device 10 .
  • the difference signal ⁇ i supplied by the adder 2 represents the so-called.
  • Prediction error which is now DCT-transformed, quantized and encoded via devices 3 - 5.
  • a receiver which can determine and display the image information of the current image as a result of the received prediction error and the image data or image information of a previous image.
  • the transformed and quantized prediction fields ⁇ i are in turn subjected to an inverse quantization and an inverse DCT transformation via the devices 6 and 7, so that the image information 8 of the motion compensation device 10 always depends on the predicted image information i 'of the motion compensation device 10 Image can be saved.
  • there is an automatic adjustment of the image sharpness ie an automatic adjustment of the quality of the image to be processed.
  • the motion vectors v supplied by the motion estimation device 9 are evaluated, depending on the motion vector or the motion vectors v, it is recognized whether the image to be transmitted has a lot or little movement, in particular fast, in relation to the previous image or contains slow movements.
  • the image sharpness is automatically reduced in order to reduce the amount of data to be processed. Conversely, the image sharpness is increased for an image with little movement, because in contrast to images with a lot of movement, the human eye would perceive a lower sharpness in this case.
  • This automatic adjustment of the image sharpness according to the present invention ensures that, on the one hand, the best possible image quality perceptible by the human eye and, on the other hand, the greatest possible reduction in the data to be processed is ensured.
  • an analysis device 12 is provided according to FIG. 1, to which the motion information v, ie the motion vectors v generated by the motion estimation device 9, are supplied.
  • the analysis device 12 analyzes and monitors the motion vectors v and, by evaluating the respective motion vector v, determines whether there is a lot or little motion in the image to be processed compared to the previous image.
  • the analysis device 12 thus evaluates the shift contained in the motion vector v between two successive images and assesses the motion corresponding to the shift. This decision can be made in particular depending on the size of the amount and / or the direction of rotation of the respective motion vector v.
  • the analysis device 12 merely provides a yes / no decision regarding the presence of a fast or slow movement. More precise, however, is an analysis device 12, which delivers and enables a graded assessment of the degree of motion contained in the current image, so that a correspondingly precise adjustment of the image sharpness can be realized depending on several different degrees of motion.
  • a control device 13 is provided for adjusting the image sharpness.
  • the control device 13 receives from the analysis device 12 information about the degree of movement contained in the current image, ie in particular information about whether the current image contains a lot or little movement or fast or slow movements compared to the previous picture.
  • the control device 13 acts on certain parameters of the arrangement shown in FIG. 1 in order to adapt the image sharpness to the determined degree of movement.
  • the human eye cannot precisely identify blurred images with faster movements. This fact is used in accordance with the present invention to the effect that the sharpness of the image is reduced more and more as soon as an increasing degree of motion is found in the image to be processed.
  • the present invention ensures that there is always sufficient image sharpness, since In this case, the human eye can very well recognize blurred images.
  • quantization parameters of the quantization device 4 are set by the control device 13 to influence the image sharpness. For example, when an image is detected with fast movements, the number of quantization intervals of the quantization device 4 can be reduced, so that the image sharpness is reduced and the amount of data to be processed is reduced. Conversely, if faster movements are detected in the image to be processed at the moment, the number of quantization intervals of the quantization device 4 can be selected to be relatively high in order to ensure sufficient image sharpness.
  • the control device 13 sets certain filter parameters of the pre-filter device 14 or the corresponding pre-filter algorithm. The control takes place in such a way that when a lot of movement is detected in the image to be processed at the moment, more image information is filtered out than in an image in which few movements are contained. This ensures that the amount of data to be processed is reduced in the case of images with larger movements in which the human eye is less able to perceive blurring, while in the case of images with Slower movements are sufficiently sharp.
  • control of the pre-filter device 14 is carried out by the control device 13 in addition to the control of the quantization device 4.
  • the control device 13 it is of course also possible to use only one of the two controls to adjust the image sharpness, i.e. the image quality to provide.
  • the proposed automatic focus adjustment can also be done with an automatic refresh rate adjustment, i.e. temporal image resolution can be combined.
  • an automatic refresh rate adjustment i.e. temporal image resolution can be combined.
  • the image repetition rate can be increased after ascertaining a fast movement and decreased in the case of a slow movement in order to always be able to achieve an optimal image quality which is adapted to the actual circumstances.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

L'invention concerne un procédé pour comprimer des informations image à l'aide d'une estimation de mouvement. Des vecteurs de mouvement (v) représentant le mouvement d'une image instantanée par rapport à l'image précédente sont ensuite générés sur la base de ladite estimation de mouvement. Le degré de mouvement contenu dans le décalage entre l'image instantanée et l'image précédente est évalué en fonction des vecteurs de mouvement (v), et la définition d'image est ensuite réglée en fonction de l'évaluation du de gré de mouvement. La définition d'image est réduite pour des mouvements rapides et accrue pour des mouvements lents. Le nombre d'intervalles de quantification ou bien de certains paramètres de filtrage pour préfiltrer les informations image peut être ajusté par exemple en fonction du degré de mouvement déterminé.
PCT/DE1998/002249 1997-08-29 1998-08-05 Procede pour comprimer des informations image WO1999012356A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19737835.8 1997-08-29
DE19737835A DE19737835C2 (de) 1997-08-29 1997-08-29 Verfahren zum Komprimieren von Bildinformationen

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WO1999012356A1 true WO1999012356A1 (fr) 1999-03-11

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Cited By (1)

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US6501797B1 (en) 1999-07-06 2002-12-31 Koninklijke Phillips Electronics N.V. System and method for improved fine granular scalable video using base layer coding information

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DE10238019A1 (de) * 2002-08-20 2004-03-11 Diehl Munitionssysteme Gmbh & Co. Kg Verfahren und Vorrichtung zur Echtzeit-Geländeaufklärung
US7889792B2 (en) 2003-12-24 2011-02-15 Apple Inc. Method and system for video encoding using a variable number of B frames

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EP0563778A1 (fr) * 1992-03-25 1993-10-06 Intel Corporation Méthode et appareil de codage d'images sélectionnées à une résolution inférieure
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