WO1996029818A1 - Transmission progressive d'images - Google Patents

Transmission progressive d'images Download PDF

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Publication number
WO1996029818A1
WO1996029818A1 PCT/GB1996/000623 GB9600623W WO9629818A1 WO 1996029818 A1 WO1996029818 A1 WO 1996029818A1 GB 9600623 W GB9600623 W GB 9600623W WO 9629818 A1 WO9629818 A1 WO 9629818A1
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WO
WIPO (PCT)
Prior art keywords
image
resolution
workstation
information
server
Prior art date
Application number
PCT/GB1996/000623
Other languages
English (en)
Inventor
Anil Bharath
Richard Kitney
Original Assignee
Imperial College Of Science, Technology & Medicine
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 Imperial College Of Science, Technology & Medicine filed Critical Imperial College Of Science, Technology & Medicine
Priority to AU50122/96A priority Critical patent/AU5012296A/en
Publication of WO1996029818A1 publication Critical patent/WO1996029818A1/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
    • H04N19/30—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
    • H04N19/36—Scalability techniques involving formatting the layers as a function of picture distortion after decoding, e.g. signal-to-noise [SNR] scalability
    • 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
    • H04N19/60—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
    • H04N19/619—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding the transform being operated outside the prediction loop
    • 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
    • H04N19/63—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/16—Indexing scheme for image data processing or generation, in general involving adaptation to the client's capabilities
    • 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
    • H04N19/30—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2201/00—Indexing scheme relating to scanning, transmission or reproduction of documents or the like, and to details thereof
    • H04N2201/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
    • H04N2201/3201—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
    • H04N2201/3225—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to an image, a page or a document
    • H04N2201/3226—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to an image, a page or a document of identification information or the like, e.g. ID code, index, title, part of an image, reduced-size image

Definitions

  • the invention relates to progressive transmission of images, and in particular although net exclusively to the progressive transmission of medical images across a computer network from a server to a workstation.
  • the images may be stored in digital form on a central server so that they may be called up as required by the user on a local workstation or display client.
  • One method of dealing with this problem is to present the user with a set of small " thumbnail" images, each of which is a low-resolution version of one of the images of the set the user is interested in.
  • the user selects the required image using the displayed thumbnail images, the required image then being sent in higher- resolution form from the server to the workstation.
  • the image information may be updated from a low-resolution thumbnail image to a high-resolution display of the same image.
  • the first way is to retransmit the full content of the high-resolution image. This represents a wastage of bandwidth, since some of the image information is already present at the viewing console.
  • the second way in which the display may be updated is to transmit only the difference between the current image resolution and the desired high-resolution image from the server to the workstation.
  • the retransmission of full resolution images represents a potential problem: for an individual image the retransmission of the full resolution image may not be significant; for the case in which there are many active viewing consoles, and a steady traffic of viewing and selection operations, the retransmission of the entire image may represent a significant bandwidth requirement over the transmission of the detail only.
  • a method of progressively transmitting images across a computer network from a server to a workstation comprising.
  • the method of the present invention is particularly although not exclusively of use in the hospital environment, for the transmission of medical images such as echocardiographic images.
  • medical images such as echocardiographic images.
  • the present invention allows the individual images making up the mosaic to comprise small low-resolution "thumbnail" images.
  • a user who wishes to see more detail for one particular image simply selects the image (for example by clicking on it using the mouse). Further detail is then sent from the server, this further detail being combined with the information already held at the workstation to produce a slightly higher resolution image.
  • Yet further information may be requested from the server if the user needs to see an even higher resolution version of the image.
  • the only information that needs to be transmitted across the network is the detail information, that is the difference between the current low-resolution version of the image already held at the workstation, and the required higher-resolution version.
  • the information may be sent automatically from the server.
  • a specific request may be sent by the workstation to the server each time further information is required. This request may conveniently be user-generated.
  • the preferred encoding method is to use the orthogonal wavelet transform.
  • This is a transform which is discrete in both the time domain and in the scale-space (wavelet) domain.
  • the small extent of the functions in the spatial domain allows for rapid convolution.
  • the orthogonal nature of the functions used in the preferred embodiment guarantees that the minimum amount of information needs to be sent across the network.
  • the user may select a desired area of the image which he or she wishes to see in more detail.
  • a desired region could for example be picked out on the screen with a mouse, preferably by dragging a box over the area of interest. If only an area of the image is selected by the user, the server sends information only on that selected area across the network.
  • the invention extends to a computer network and/or system for operating the method of the present invention.
  • the computer network may comprise a local area network or a wide area network, connected by wires or by a wire-less link.
  • the term "network” includes any means of remote communication between computers, and accordingly encompasses (without limitation) communication via the telephone system and/or satellites. Such means of remote connection may be useful where for example the server is in a different hospital, and perhaps even in a different country, from the workstation.
  • Figure 1 is a block diagram showing, schematically, the operation of the discrete wavelet transform
  • Figure 2 (a) shows the discrete wavelet transform decomposition process
  • Figure 2 (b) shows the decimation process at successive scales
  • Figure 3 shows the Daubechies 4, 12 and 20 scaling functions, evaluated at different respective scales
  • Figure 4 illustrates the decimation process in graphical form
  • Figure 5 shows how the multi-resolution image may be stored.
  • the preferred embodiment of the present invention is a method and/or system for the progressive transmission of medical images from a remote file server to a local workstation.
  • Each image is stored on the server in a multi-resolution format comprising a low-resolution representation which may be called up as a small "thumbnail” image en the workstation, and a plurality of "detail" representations. If the user wishes to see the image at lowest resolution, the thumbnail image alone is sent. If, having viewed the thumbnail image, the user wishes to receive a higher-resolution representation, the first "detail" representation is passed along the network to the workstation.
  • the "detail" representation is added to the low-resolution image to provide the required higher-resolution image
  • the user can call upon the next "detail" representation, stored on the server, which in a like manner is added to the information which has previously been passed to the workstation to provide an image at the next highest resolution. The process may be continued until the user has the image resolution he or she requires, or has an image of the maximum resolution which is available from the server.
  • the first stage in the process is, of course, to take an original image and to encode it in digital form in a digital data file which forms the multi-resolution representation that is actually stored on the server.
  • the preferred embodiment uses the orthogonal wavelet transform.
  • the orthogonal wavelet transform is a discrete transform, similar to the Foulier transform but instead of using sin functions wavelet mother functions are used instead.
  • Each wavelet mother function has a limited extent in wavelet space, which contrasts with the s in functions used for Foulier transforms which are of course infinite in extent.
  • the wavelet transform has the following general form:
  • the discrete wavelet transform which is used here, is the same, except that the values of a and b are restricted to discrete values only.
  • orthogonal wavelets are chosen, for example the Daubechies wavelets shown in Figure 3.
  • the advantage of the present scheme is that the full set of coefficients or weights W(a,b) can be arranged into a multi-resolution representation of the original signal.
  • f(n) is a discrete signal to be approximated
  • f'(n) is calculated by determining the mean of adjacent samples within f(n). For example, f'(0) is half the sum of f(0 ) and f(1). Likewise, f'(1) is half the sum of f(2) and f(3). F' (n) may therefore be considered as an approximation g(n) to f(n).
  • h(n) the difference between f(n) and g(n).
  • the process may be repeated, decimating the sample each time, thereby creating a plurality of individual "detail" representations, each indicative of the difference between the current approximation and the last previous approximation.
  • the final approximated signal is kept, along with all of the detail signals.
  • the process may be represented schematically at each stage by the block diagram shown in Figure 1.
  • an approximation signal g(n) and a detail signal h(n) is determined from the input signal.
  • the approximation signal is then fed back into the output and a further approximation and a further detail signal obtained.
  • the final very low-resolution g(n) output is retained, along with ail of the detail outputs h(n).
  • the structure shown in Figure 1 can be used for multi-resolution orthogonal biorthogonal, or quadrature mirror filters (QMF) where each of the above cases is specified by the chosen filter coefficients.
  • QMF quadrature mirror filters
  • the filters are simply denoted as low pass, g(n) and high pass, h(n), to present a general form, but in fact these filters are related to scaling function, ⁇ (x), and wavelet function ⁇ (x) [2] .
  • the decomposition process is illustrated in Figure 2.
  • Each block has both a low pass filter and a nigh pass filter.
  • the output of each filter is decimated by a factor of two.
  • the resolution of the output of the low pass filter is also changed because of losing nigh frequency detail.
  • the output of the filter chain, A 2 -m S, signal represents a discrete approximation of signal at the resolution 2 -m .
  • the other output is called the detail signal, D 2 -m S, at the resolution 2 -m .
  • D 2 -m S the detail signal
  • the discrete wavelet representation has the same total number of samples as the original signal.
  • the smoothness of A2 j S depends on the shape of the scaling function. In general we would wish to have a smooth scaling function, but this function should satisfy some conditions such as orthogonality, support width etc.
  • One of the important things is the spatial support (width) of the scaling function which divides the wavelet transform into compact into compact and non-compact wavelets.
  • a multi-resolution decomposition is a method of representing signals at different scales of magnification.
  • the concept of multi-resolution decomposition was initially developed by Mallat [2] to address the problem of characterising image scenes in a scale independent manner.
  • the approach of Mallat is essentially a pyramidal decomposition, along the lines of Burt and Adelson, but uses values of h(n) and g(n) such that the decomposition is onto an orthogonal basis.
  • the basic idea is that of successive approximation, together with adding detail signal from one approximation to the next. Assume that we have a ladder of spaces such that
  • W. contains the detail signal necessary to go from V 1 to V 1+1 . If we have an approximation of a signal at a resolution corresponding to V 0 , then a better approximation to the signal is obtained by adding the detail signal corresponding W 2 . This detail signal is the projection of the signal in W 2 .
  • This interpolation is a convolution between the scaling function ⁇ and
  • This particular interpolation represents an example in going from a representation of the signal at one scale to an approximation of the signal at the scale immediately above it. If we wish to go from a representation of the signal at, say, a scale of 2 -j to an approximation of the signal at some scale 2 -j+1 , where l>1, it is necessary to dilate the scaling function appropriately.
  • the appropriate dilation may be performed as follows: if the scaling function of Equation (1 ) is at the resolution 1(i.e. 2 -1 ), then it belongs to V 0 . Since one may write
  • This equation may be generalised to relate the scaling function at a scale 2 to the scaling function at a resolution 2 j+1 for any j. Therefore,
  • the two-dimensional transform may again be represented by a repeated function block where, instead of a pair of outputs, we have four outputs corresponding to the low-frequency image component and the high-frequency vertical, horizontal and diagonal components. The latter three image components correspond to the detail signals.
  • Figure 5 shows, in schematic form, how the information may be stored in a data file on the server.
  • the lowest resolution image that is expected to be required (A) is stored, along with the sequences of detail information D 1 , D 2 and D 3 . If, for example, the lowest resolution image A is an 8 ⁇ 8 image, one will automatically obtain from the algorithm three sets of detail signals each of which also has size 3 ⁇ 3. The next level up is 16 ⁇ 16, and so on. To produce an image of 16 ⁇ 16 resolution , the three detail signals D 1 are added into the low-resolution image A. Similarly, to create an image of 32 ⁇ 32 resolution, the detail images D 2 are added onto the previously-created 16 ⁇ 16 image.
  • the infrastructure of orthogonal, multiresolution image decomposition provides an efficient way of doing this, in terms of bandwidth requirements.
  • a region of interest such as a heart valve on a cardiac image.
  • the present infrastructure allows one to view that region at full resolution without needing to increase the resolution outside of the specified region.
  • the user first selects an area of interest (for example using a mouse), and that area is then redrawn on the screen in greater detail. For example, if the user wishes to view in more detail only the top left-hand corner of the thumbnail image A, he or she simply selects that area and a signal is sent to the server instructing it to send further detail appropriate to that area only. With the file structure shown in Figure 5, the server would send only the detail information contained within the top left-hand corners of each of the three D 2 images. If the user then wishes to view that enlarged image in yet more detail, the server would send only the top left- hand corners of the D 2 images.
  • an area of interest for example using a mouse
  • a general implementation involves tracing all of the influenced children of a pixel throughout the various components of the image in the transform space.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Compression Of Band Width Or Redundancy In Fax (AREA)

Abstract

L'invention concerne un procédé de transmission progressive d'images d'un serveur à un poste de travail consistant à coder l'image dans un format multi-dimensionnel, à utiliser une transformation orthogonale d'ondelette et à mémoriser l'image codée en tant que fichier numérique sur le serveur. Un utilisateur demandant l'image au niveau d'un poste de travail voit d'abord un tracé miniaturisé. S'il souhaite davantage de détails, il en fait la demande au serveur qui fournit une image détaillée constituée uniquement des informations nécessaires pour améliorer l'image basse-résolution en une image de résolution supérieure. Cette approche économise la transmission par le réseau d'informations déjà envoyées en relation avec l'image originale basse-résolution. Le système peut être d'une utilité particulière dans les hôpitaux, pour la transmission d'images médicales.
PCT/GB1996/000623 1995-03-17 1996-03-15 Transmission progressive d'images WO1996029818A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU50122/96A AU5012296A (en) 1995-03-17 1996-03-15 Progressive transmission of images

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB9505469.8 1995-03-17
GB9505469A GB9505469D0 (en) 1995-03-17 1995-03-17 Progressive transmission of images

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WO1998003008A1 (fr) * 1996-07-16 1998-01-22 Ericsson, Inc. Procede de transmission d'images a resolutions multiples dans un systeme de telecommunications a frequence radio
US5940117A (en) * 1996-07-16 1999-08-17 Ericsson, Inc. Method for transmitting multiresolution image data in a radio frequency communication system
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AU732949B2 (en) * 1996-10-30 2001-05-03 Algotec Systems Ltd. Data distribution system
WO1998019263A1 (fr) * 1996-10-30 1998-05-07 Algotec Systems Ltd. Systeme de distribution de donnees
EP1420362A2 (fr) * 1997-01-09 2004-05-19 Canon Kabushiki Kaisha Agrandissement utilisant les grandeurs prédéterminees pour vignettes
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