APPARATUS AND METHOD FOR OPTIMIZED COMPRESSION OF INTERLACED MOTION IMAGES

Abstract: An interlaced image processing module receives interlaced first and second fields (355a) and produces a reference field and error field (360a). The reference field corresponds to the still image content, whereas the error field corresponds to the motion content between fields. Motion between fields is thus represented in the error field (E), without redundant representation of the still image content provided by the first field. Where there is little motion between fields, the error terms are small so the predictor (315a) preserves the coding efficiency provided by any auto-correlation in the image. The interlaced image processing method does not rely on pixel group classification, thus avoiding classification errors and the loss of coding efficiency from still image content in motion classified blocks. Problems of relative motion between fields and local artifacts are avoided. Another embodiment transforms the interlaced fields into frame data having high frequency and low frequency fields.

Description: APPARATUS AND METHOD FOR OPTIMIZED COMPRESSION OF INTERLACED MOTION IMAGES BACKGROUND OF THE INVENTION 1. Field of the Invention This application relates generally to digital image signal processing, and more particularly to the compression of interlaced motion images. 2. Description of the Related Art Image and motion image signals are increasingly being processed in the digital domain. One set of problems encountered in digital image signal processing result from signal formats used in conventional analog video processing. For example, certain formats, particularly conventional broadcast television, implement signal interlacing. In video interlacing, a frame is comprised of two separate rasters. A first raster comprises a series of lines in the frame, and a second raster comprises scan lines that reside between the lines from the first raster. The first and second rasters can respectively be referred to as first and second fields. Thus, the video signal can be said to include a series of frames, with each frame including first and second interlaced fields. There are various problems introduced by interlaced motion images and the conventional processing methods. For example, interlaced images may have relative motion between the rasters, which does not correlate well vertically. One solution to this could be to encode images with significant motion by frame. However, this would result in very inefficient image encoding. Alternatively, images can be processed by field to allow for poor vertical correlation in the case of motion. However, if this is done, the encoding advantage of any high correlation in still areas is lost, again resulting in inefficient encoding. Additionally, if images are processed by field, slight variations in DC errors or quantifier linearity will cause horizontal stripes in a motion free fame viewed as a still. Typically, block based compression schemes (such as MJPEG and MPEG) treat the interlaced video decorrelation problem on a block level. Thus, each block in a frame is classified as a motion block or a still block. The still image blocks are processed differently from the motion blocks. There are various problems with the block based approach. Particularly, block based motion analysis can generate boundaries and visual artifacts due to incorrect motion estimation decisions. Also, block based motion analysis can generate very large local errors, making it unsuitable for applications where local error bounds are desired, as in medical, technical or critical production applications. Finally, the block based approach can cause an obvious discontinuity or defect where an object in motion spans adjacent blocks, particularly where one block is still processed while an adjacent block is motion processed. Thus, there remains a need for digital image signal processing, particularly processing incorporating lossy compression, that addresses the problems introduced by frames having interlaced fields. SUMMARY OF THE INVENTION The present invention provides an apparatus and method for optimized compression of motion images having frames with interlaced first and second fields which avoids the inefficiencies and inadequacies of conventional schemes, including block based approaches. In one embodiment, the apparatus and method for interlaced motion image compression provides predicted image frames having a reference field and an error field from the interlaced motion image frames. The reference field can be one of the first and second fields in the interlaced frame. Thus, the reference field has the same values as, for example, the first field. The reference field provides the still image content of the frame, preferably on a value by value basis. The error field provides the motion image content of the frame on a value by value basis. Specifically, for the values corresponding to each location in the prediction field, the error field provides a value corresponding to the motion between fields. The error field can be obtained by first obtaining a prediction field that provides what the non-reference field (e.g., the second field) would be if there were no motion between the first and second fields. Then, the error field is determined using the difference between the second field and the prediction field. The first and second fields are easily recovered from the predicted frame data. One of the fields (e.g., the first) is determined to be the reference field, which is part of the predicted image frames. The remaining field is obtained by summing the prediction and error fields, thus reversing the forward interlaced image processing steps. In image processing, still content in a frame can be efficiently encoded, as it is highly correlated. The interlaced motion image compression scheme takes advantage of any and all coding efficiency provided by auto-correlation, because the values in the error field corresponding to still portions of the frame will be small. This is in marked contrast to the block based approach, which can often predict a block having substantial still portions to be a motion block and thus lose the coding benefit of the still portions. The apparatus and method for interlaced image processing also solves various other problems present with conventional schemes. For example, the image is processed as a continuous function, and so avoids discontinuous artifacts, and alleviates problems related to motion between fields, since the reference field provides the still content for both fields, and the error field provides the relative motion between the fields. Another embodiment of the apparatus and method for interlaced motion image compression receives frames having geometrically interlaced first and second fields and uses a vertical transform to produce frames having high and low frequency fields that each correspond to the first and second fields. Vertical transformation according to this embodiment groups lines together in time to provide good motion correlation. Additionally, the auto-correlation in the frame from still portions is taken advantage of through the reduced magnitude of high band components. The present invention has other advantages and features which will be more readily apparent from the following detailed description of the invention, in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic illustrating a computer including an embodiment of an interlaced image processing module for compressing interlaced motion images in accordance with the present invention. FIG. 2 is a flow diagram illustrating a method for processing video signals including an embodiment of a method for compressing interlaced images in accordance with the present invention. FIG. 3 is a schematic illustrating an embodiment of an interlaced image processing module constructed in accordance with the present invention. FIG. 4 is a flow diagram illustrating an embodiment of a method for forward processing of interlaced images in accordance with the present invention. FIG. 5 is a flow diagram illustrating an embodiment of a method for reverse processing of interlaced images in accordance with the present invention. FIG. 6 is a schematic illustrating another embodiment of an interlaced image processing module constructed in accordance with the present invention. FIG. 7 is a flow diagram illustrating another embodiment of a method for forward processing of interlaced images in accordance with the present invention. FIG. 8 is a flow diagram illustrating another embodiment of a method for reverse processing of interlaced images in accordance with the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Referring now to the block diagram of FIG. 1, a computer 100 incorporating an embodiment of an interlaced image processing module 180 constructed in accordance with the present invention is shown. The computer 100 includes a CPU 112, memory 114, display device 116, data storage device 118, input/ output ports 120 and communications interfaces 122. The CPU 112 is arranged to execute instructions, such as those stored in memory 114, which may be a conventional RAM or any conventional memory for storing instructions for execution by the CPU 112. The display device 116 is conventional, such as a CRT, LCD or LED type display. Various conventional hardware for storing data may be used for the data storage device 118, such as a hard disk, or a tape drive. The input/ output ports 120 are also conventional, and can be arranged to input and 4 output video signals, such as interlaced motion image signals (e.g., NTSC broadcast television format). Although it is understood that the computer may operate as a stand alone, the communications interfaces 122 allow the computer 100 to communicate with other computers on a local area network, other computers over the Internet, etc. Thus, the communications interfaces 122 can include a modem and/ or network interface card for facilitating such communication. The CPU 112, memory 114, display device 116, data storage device 118, input/ output ports 120 and communications interfaces are arranged in a conventional computer architecture. The computer 100 can be a personal computer with an operating system and various applications, including the multimedia signal processing application 150. Alternatively, the computer 100 can be a dedicated video recorder, also including the functionality of the multimedia signal processing application 150, the image signal processing module 175 and its components, but not necessitating certain personal computer features. Various conventional architectures for predicting an interlaced motion image signal according to the functionality described herein will be recognized by the artisan. The multimedia signal processing application 150 includes routines for processing audio and image signals. The application 150 includes an interlaced image processing module 180, a transform module 185, a quantification module 185, and a coding module 195. Although in this embodiment the application 150 is implemented as software, it is understood that the functionality of the application 150, including that of the various modules 180, 185, 190, 195, can be implemented in hardware, or a combination of hardware and software. Referring now to the flow diagram of FIG. 2 along with FIG. 1, a method of image signal processing performed by the image signal processing module 175 illustrates how a video signal can be input to, forward processed, stored (or transmitted in compressed form), reverse processed, and output from the computer 100. The flow diagram of FIG. 2 conceptually illustrates the flow of data and the operations performed on the data. The various modules 180, 185, 190, 195 in the image signal processing module 175 perform the operations, which are numbered accordingly. For example, the interlaced image processing module 180 performs the operations 180a, 180b shown in FIG. 2. The signal originating from a video source (e.g. a conventional analog broadcast video signal), after some initial conventional processing, can be input to a frame buffer (not shown). The frame buffer temporarily stores frames of image data. Multiple frames can be stored in each buffer so that the data available for processing does not become exhausted when one module processes faster than another. The frame buffers can be arranged as a conventional FIFO buffer, and can be provided in memory, or, alternatively, can be register based. As shown in FIG. 2, the digital image signal is subjected to forward interlaced image processing 180a, then transformation 185a, quantification 185a, and encoding 190a. For forward interlaced image processing 180a, digital image data having frames including first and second fields are processed. In one embodiment, the second field is predicted using the first field as a reference, and forward interlaced image processing 180a produces frame data comprising the first field and an error field. In another embodiment, the first and second fields are used to produce low and high band information corresponding to each frame. The functionality of the interlaced image processing module 180 is described further below. The transform module 185, quantification module 190 and coding module 195 implement conventional image processing techniques for the illustrated forward tr.ansform 185a, quantification 190a and encoding 195a operations. Basically, the forward transform 185a conditions the image data for further processing. Various conventional transforms can be used for the transform operation, such as a wavelet transform. The quantification operation 190a provides data values for the transformed image data according to the selected quantification scheme (e.g. 12-bit). The encoding operation 195a provides encoded image data which is compressed for more efficient storage, transmission, or other processing. Conventional encoding schemes for compressing the amount of data required to represent the quantified data, such as Huffman coding, can be implemented by the coding module 195. It is understood that various alternatives for the forward transform 185a, quantification 190a, and encoding 195a operations will be available to the ordinarily skilled artisan. One such alternative for encoding is described in patent application Ser. No. 60/052,144, filed by Kenbe Goertzen on June 9, 1997, entitled Apparatus and Method for Entropy Coding. Various operations can be performed using the compressed image signal data produced by forward interlaced image processing 180a, transformation 185a, quantification 190a and encoding 195a. For example, the data can be stored 118a, for example, in a data storage device 118 such as a hard disk. Alternatively, the compressed image signal data can be transmitted from one point to another, such as from one computer to another over a LAN, a modem, or the Internet, or otherwise. Finally, a reverse process to that described above, where compressed digital image signal data is decoded 195b, reverse quantified 190b, reverse transformed 185b, and reverse interlaced image processed 180b to produce video output is also shown in FIG. 2. FIGs. 1 and 2 illustrate an example of where the interlaced image processing module 180 and corresponding forward and reverse processing schemes could be implemented in image signal processing. Thus, the features associated with the interlaced image processing module 180 in the example, such as the quantification module 185, can be optionally excluded. For example, the computer 100 can include an interlaced image processing module 180 alone, such that interlaced image data subjected to forward processing may be provided to a conventional mechanism for processing such data, such as an image CODEC. The interlaced image processing module 180 and corresponding forward and reverse prediction processing methods are now further described. Referring to the block diagram of FIG. 3, an embodiment of an interlaced image processing module 180' for providing the above described operations includes a signal management module 310, a prediction field determination module 315, an error field determination module 320, and a field recovery module 325. The signal management module 310 includes a signal dividing module 355 and a signal merging module 360. Referring now to the flow diagram of FIG. 4 along with FIG. 3, an embodiment of a method for forward processing of interlaced images 400 implemented by the interlaced image processing module 180' is described. The interlaced image processing module 180 receives geometrically interlaced frames. The interlaced frames include a first field (V F ) and a second field (Vs). The interlaced image processing module 180 then produces non-interlaced frames comprising a reference field (e.g., VF) and an error field (e.g. E). The reference field corresponds to the still image content of the predicted frame, whereas the error field corresponds to the motion content between fields. First, the geometrically interlaced frame (VF, VS) is received by the signal divide module 355, which parses the signal (signal divide 155a) to produce the first field (VF) and the second field (Vs). One of the fields is designated to be the reference field. In FIG. 4, the first field is shown as the reference field, but it is understood that the second field can alternatively be used as the reference field. The reference field is then used by the prediction field determination module 315 to produce a prediction field (Fig. 4, functional block 315a). The prediction field is a determination of what the image data corresponding to the second field (or whatever field is not the reference field) would be if there were a substantial lack of motion between the first field and the second field. This provides a prediction field corresponding to the second field. The error field determination module 320 then produces an error field using the prediction field and the second field. Preferably, the difference between the second field and the prediction field is used to produce the error field. The signal merging module 360 then merges the first field and the error field to produce frames of predicted image data, which can also be referred to as frames of compressed image data. Preferably, the compressed image data frames are not interlaced in time. In other words, the values corresponding to the first field are temporally segregated from the values corresponding to the error field. In a sequential approach this would mean that for the compressed image data frame, a stream of first field values would first be encountered, followed by a stream of error field values (or vice-versa). Since the prediction field corresponds to a second field that is assumed to have no motion, the error field thus, substantially correlates to the motion between frames, and provides such information very efficiently. Also, the reference field provides an efficient representation of the still image content in the image. Referring now to the flow diagram of FIG. 5, an embodiment of a method for reverse processing of interlaced images 500 implemented by the interlaced image processing module 180' is described. Previously produced predicted frame data can be provided to the signal divide module 355 for parsing into the first field and the error field. Then the prediction field determination module 315 produces a predicted field from the first field, preferably using the same functionality as used in the forward interlaced image processing scheme. The second field is then recovered by the field recovery module 325, preferably by adding the error field to the prediction field. Thus, the first field and the second field are provided, and can be conventionally merged by the signal merging module 360 to produce frames of interlaced first and second fields. Table 2 is an exemplary illustration of the interlaced image processing scheme. Preferably, the interlaced image processing module 180 uses a transform which consists of a half band predictor to predict the second field from the first, and then generates the error terms between that prediction and the second field values as described above. The resulting frame data then consists of the initial field, followed by the second field represented as a prediction error. This transform has been found to provide apparent near perfect motion compensation and compression efficiency. Table 2: Frame Line Original Data Transformed Data Line In Phase 1 1111111111111111 1111111111111111 1 2 2222222222222222 1111111111111111 3 3 1111111111111111 1111111111111111 5 4 2222222222222222 EEEEEEEEEEEEEEEE 2 5 1111111111111111 EEEEEEEEEEEEEEEE 4 6 2222222222222222 EEEEEEEEEEEEEEEE 6 There are various advantages provided by the interlaced image processing module 180' and corresponding method of processing interlaced images. For example, the method can transform n bit data in an n bit system exactly. Additionally, the method is hardware efficient, in that it requires a minimum of processing logic and memory bandwidth to support it. The method is continuous, so it does not generate discontinuous artifacts, and it is very efficient because it does not group pixels, and thus, it avoids the potential for incorrect classification. Further, the method is interpolative and balanced (linear phase), so it does not produce the potential for vertical motion artifacts present in other methods. The method is very local, so it does not produce the potential for vertical ringing, tiling, smearing, or backward movement in time of information present in other methods. Finally, this method provides the added benefit of making it is easy to convert odd fields to even, or even fields to odd. Additionally, various problems encountered with conventional interlaced motion image processing are alleviated. The problem of relative motion between the rasters is alleviated because frames with motion content between fields become areas of large prediction errors in the second (predicted) field, but the values are grouped so that they correlate well horizontally and vertically. The low coding efficiency due to motion experienced using conventional techniques is prevented because highly correlated (largely still) images will produce a prediction field having small error terms, thus preserving the coding efficiency of highly correlated stills. Further, the potential problems introduced in conventional field based processing, including those introduced by variations in DC error or quantifier linearity, are avoided because the second field is reconstructed using the low frequency information from the first field. This prevents any raster separation of field in a still frame. The error field effectively contains no low frequency information, so there is no frequency disagreement with the first field. This avoids horizontal stripes and localized interlaced separations in interlaced still information. This approach also processes the entire image as a continuous function, so there is no possibility of discontinuous artifacts generated due to motion analysis decisions 10 or decision regions. This further avoids the inefficiency resulting from grouping pixels, where any group which does not have exactly the same motion characteristics will not be optimally encoded. Also, with conventional approaches, small portions of images can present very large errors due to incorrect motion decisions, or regions which are not motion homogenous. Due to the continuous nature of this approach, large localized errors are completely avoided. There are some additional subtle advantages to the prediction approach. One is the lack of "bounce" due to image artifacts moving in time. Sub-band transforms under heavy quantification cause a mixing of the first and second field information. This combination of temporal and spatial information causes the two fields to approach each other, which results in the appearance of slight field misplacement. One field appears to move slightly downwards and the other moves slightly upwards. This results in bouncy instead of linear vertical motion. Since the first field can remain unchanged (if it is the reference field), the prediction approach prevents artifacts from moving backward in time. An additional benefit of this approach is that the interlaced image processing module can also be used to convert even fields to odd fields or odd fields to even. This can be done by converting the first field to a second field, and vice-versa, as follows. To convert the first field to a second field, the half band predictor is used to predict the second field as a π/2 vertical phase shift from the first field. To convert a second field line to a first field line, the half band predictor is used to predict a π/2 vertical phase shift in the error function, which is added to the first field line in that position. As described above, a half band predictor is preferably used to predict the second field from the first field. The first and second fields can be represented in two dimensional geometrical space as VF (X, y) and Vs (x, y), where y represents the row and x represents the column in a frame. If the first field pixels in the row above and below the second field pixel to be predicted are referred to as VF[X, -n..n] where VF[X, - 1] is just above and VF[X, 1] is just below the second field pixel to be predicted (Vs[x, 0]), then the following half band predictors can be used: P[x, 0] := (V F [x, -l] VF[X, 1]) * ( 1 1 ) / 2 ; or 11 P[x, 0] := (VF[X, -3] VF[X, -1] VF[X, 1] V F [x, 3]) * ( -1 9 9 -1) / 16 ; or P[x, 0] := (VF[X, -5] .. V F [x, 5]) * ( 3 -25 150 150 -25 3) / 256 ; or P[x, 0] := (VF[X, -7] .. VF[X, 7]) * ( -5 49 -245 1225 1225 -245 49 -5) / 2048. The above half band predictors are provided by way of example. It is understood that any half band predictor could be provided, or that the predicted field could be produced using other transforms or schemes, preferably those that offer a prediction of what the second field would be if there were no motion between fields, using the first field as a reference (or vice-versa). The error field is then determined as the difference between the second field and the predicted field, such as according to the following equation: E[x, 0] := Vs[x, 0] - P[x, 0]; (* error calculation *) Finally, in a reverse prediction flow, the second field is reconstructed according to the following equation: Vs[x, 0] := E[x, 0] + P[x, 0] ; (* value reconstruction *) The above equations correspond to the value in column x, row 0 in two dimensional geometrical space. Values in other rows and columns can be analyzed, according to the following generalized equations. p [ χ . yl := (VF[X, y-1] .. Vf[x, y+1]) * ( 1 1 ) / 2 (or alternate half band predictor); E[x, y] := Vs[x, y] - P[x, y] (* error calculation *) Vs[x, y] := E[x, y] + P[x, y] (* value reconstruction *) Various alternatives for determining the prediction field, error field and other fields can be implemented. For example, in one alternative, the range of the math system can be maintained exactly. This means that n bit per pixel component images yield n bit full resolution results. Notably, when implementing this, the resulting transform must be recorded exactly to avoid wrapping errors, because an error of one can convert a value at one extreme of the range to the other extreme. The following equations can be used for this exact form alternative: EI y] := (Vs[x, y] - P[x, y] + Range) MOD Range; Vs[x, y] := ( ( E[x, y] + P[x, y] + Range) MOD Range; 12 A scaled lossy form can also be implemented. This version maintains the range of the math system by dividing both the error field .and the first field by 2, causing a 6dB loss in resolution. If the math system has more resolution than desired in the image then this is fine. If the math system is the limit, then this process will reduce the available resolution by 6 dB. Exemplary scaled lossy equations are as follows: E[x, y] := (Vs[x, y] - P[x, y]) /2; V F [x, y] :- VF[X, y] / 2; Vs[x, y] := (E[x, y]) * 2 + P[x, y]; Vpl y] := V F [x, y] * 2. Finally, a non-linear lossy form can be implemented. For this alternative, the range of the math system is maintained by compounding the error into the original range, using nonlinear lookup and inverse lookup tables. The loss for common small values is 0 dB while the loss for much less frequent large values is about 12 dB. This approach can optimize resolution in a lossy environment. E[x, y] := LUT (V s [x, y] - P[x, y]); Vs[x, y] := ILUT (E[x, y] + P[x, y]). The interlaced image processing scheme offers substantial performance and efficiency advantages over conventional field and frame based processing. Images with significant motion can be encoded at about 50 to 70 percent of the size they would be if the image was processed as a frame, and typically with an advantage over field processing as well, whether due to correlation from still portions of the image, or low frequency correlation. Images with no motion can be encoded at within a few percent of the same size they would be if the image was processed as a frame, and with about a 30 percent advantage over field processing. The interlaced image processing scheme is not limited to processing the first and second fields in an interlaced video stream as described in accordance with the preferred embodiment. For example, the interlaced image processing scheme can also be used to allow one channel to process two or more different signals. This is accomplished by accepting an interleaved stream and placing the data in different 13 columns as it is processed. Table 2, below, illustrates the data allocation according to this alternative. Frame Field Original Data Transformed Data Field/ Line Line in Phase 1 1 CB CR CB CR CB CR CB CR CB CB CB CB CR CR CR CR 1/1 2 2 cb cr cb cr cb cr cb cr CB CB CB CB CR CR CR CR 1/3 3 1 CB CR CB CR CB CR CB CR CB CB CB CB CR CR CR CR 1/5 4 2 cb cr cb cr cb cr cb cr eb eb eb eb er er er er 2/2 5 1 CB CR CB CR CB CR CB CR eb eb eb eb er er er er 2/4 6 2 cb cr cb cr cb cr cb cr eb eb eb eb er er er er 2/6 In yet another alternative, the interlaced image processing scheme can be used to process Y Cb Cr in one channel. This is illustrated with reference to Table 3, below: Frame Field Original Data Transformed Data Field/ Line Line in Phase 1 1 Y CB Y CR Y CB Y CR Y Y Y Y CB CB CR CR 1/1 2 2 y cb y cr y cb y cr Y Y Y Y CB CB CR CR 1/3 3 1 Y CB Y CR Y CB Y CR Y Y Y Y CB CB CR CR 1/5 4 2 y cb y cr y cb y cr ey ey ey ey eb eb er er 2/2 5 1 Y CB Y CR Y CB Y CR ey ey ey ey eb eb er er 2/4 6 2 y cb y cr y cb y cr ey ey ey ey eb eb er er 2/6 14 Finally, similar rearrangements can be used for 4:2:2:4, 4:4:4 and 4:4:4:4 type image data. An additional benefit is that the same interlaced image processing module can be used to convert even fields to odd, and odd fields to even, for such applications as freeze field where the missing field of a frame needs to be generated. Referring now to FIG. 6, another embodiment of an interlaced image processing module 180" includes a signal merging module 615, a vertical transform module 620 and a reverse vertical transform module 625. As with the previously described embodiment, this interlaced image processing module 180b receives frames comprising geometrically interlaced first and second fields, and produces two fields which are not interlaced in time. However, this interlaced image processing module 180b produces a predicted frame having a low frequency field and a high frequency field. Referring now to the flow diagram of FIG. 7, an embodiment of a method for forward prediction 700 illustrates the operation of the interlaced image processing module 180b. Geometrically interlaced frames (VF, Vs) are received by the vertical transform module 620, which produces a low frequency field corresponding to both the first and second fields, and produces a high frequency field, also corresponding to both the first and second fields. Preferably, the vertical transform module 620 conducts a vertical transform of the interlaced frame before transformation, quantification and encoding. A two dimensional transform can be employed at this stage as well but it is the vertical transform which addresses the interlaced image issues. In the forward vertical transform, the resulting frame data is separated into a baseband region and a highband region, before the image is encoded. The signal merging module 615 receives the low and high frequency fields, and produces frames comprising them which are preferably not interlaced in time. Provision of the vertical transform as such groups the lines together in time, which provides good motion correlation. Additionally, any and all auto-correlation in the frame resulting from still portions is taken advantage of through the reduced magnitude of the high band components. Further, the transform is undertaken as a continuous function with no discontinuous decisions, so it does not generate the potential discontinuous results of most block based interlaced systems. 15 Table 4 is an exemplary illustration of the results of the forward vertical transform. The table includes columns indicating the frame line, original data, transformed data, and line in phase. In the example, the Is represent information in a first field, and the 2s the second. Line in phase indicates which original line the result is in phase with. TABLE 4: Frame Line Original Data Transformed Data Line InPhase 1 1111111111111111 LLLLLLLLLLLLLLLL 1 2 2222222222222222 LLLLLLLLLLLLLLLL 3 3 1111111111111111 LLLLLLLLLLLLLLLL 5 4 2222222222222222 HHHHHHHHHHHHHHHH 2 5 1111111111111111 HHHHHHHHHHHHHHHH 4 6 2222222222222222 HHHHHHHHHHHHHHHH 6 Referring now to the flow diagram of FIG. 8, the reverse vertical transform module 625 receives the frame data comprising low and high frequency fields, and performs a reverse transform on the frame data to reproduce the first and second fields, which are merged 615b into conventional interlaced frames. Various conventional sub-band transforms can be implemented for the transform processes 620, 625, including orthogonal and bi-orthogonal wavelets. Although the present invention has been described in detail with reference to certain embodiments thereof, other embodiments are possible. For example, the various modules, or functions within those modules, can be provided as hardware in lieu of software. Additionally, the interlaced image processing module could provide frame data to external resources for further processing (e.g., transformation, quantification and encoding), or could receive frame data previously parsed into first and second fields, eliminating the need for preliminary signal parsing. Further, although certain equations are provided in two dimensional space, other 16 configurations can be contemplated. Therefore, the spirit and scope of the claims should not be limited to the description of the embodiments contained herein. 17

Claims: CLAIMS What is claimed is: 1. A method for processing an image signal having frames with a first field and a second field, the method comprising: receiving image data corresponding to the first field and the second field, wherein the first field is designated to be a reference field; determining a prediction field from the reference field, the prediction field providing what the image data corresponding to the second field would be if there were a substantial lack of motion between the fields; determining an error field using the difference between the second field and the prediction field; and producing predicted frame data, the predicted frame data including the first field and the error field, the first field and the error field being non-interlaced. 2. The method of claim 1, further comprising: encoding the predicted frame data to produce encoded frame data; and recording the encoded frame data on a storage medium. 3. The method of claim 1, further comprising: encoding the predicted frame data to produce encoded frame data; and transmitting the encoded frame data. 4. The method of claim 1, further comprising: reconstructing the image data corresponding to the second field by adding the prediction field and the error field. 5. The method of claim 1, wherein the image signal is an interlaced video signal, and the first and second fields are respectively the first and second rasters in the interlaced video signals, the second raster having lines residing between the lines in the first raster. 6. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: 18 an input, for receiving image data corresponding to the first field and the second field, wherein the first field is designated to be a reference field; a prediction field determination module, in communication with the input, for determining a prediction field from the reference field, the prediction field providing what the image data corresponding to the second field would be if there were a substantial lack of motion between the fields; an error field determination module, in communication with the prediction field determination module, for determining an error field using the difference between the second field and the prediction field; and a signal merging module, in communication with the error field determination module, for producing predicted frame data, the predicted frame data including the first field and the error field, the first field and the error field being non-interlaced. 7. The apparatus of claim 6, further comprising: a field recovery module, for reconstructing the image data corresponding to the second field by adding the prediction field and the error field. 8. The apparatus of claim 6, wherein the image signal is an interlaced video signal, and the first and second fields are respectively the first and second rasters in the interlaced video signals, the second raster having lines residing between the lines in the first raster. 9. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: means for receiving image data corresponding to the first field and the second field, wherein the first field is designated to be a reference field; 19 means for determining a prediction field from the reference field, the prediction field providing what the image data corresponding to the second field would be if there were a substantial lack of motion between the fields; means for determining an error field using the difference between the second field and the prediction field; and means for producing predicted frame data, the predicted frame data including first field and the error field, the first field and the error field being non-interlaced. 10. A method for processing an image signal having frames with a first field and a second field, the method comprising: receiving predicted frame data including image data corresponding to the first field and to an error field, the error field corresponding to the difference between the second field and a prediction field of the second field; determining the prediction field based upon the first field, the prediction field providing what the image data corresponding to the second field would be if there were a substantial lack of motion between the fields; and reconstructing the second field by adding the error field to the prediction field. 11. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: an input, for receiving predicted frame data including image data corresponding to the first field and to an error field, the error field corresponding to the difference between the second field and a prediction field of the second field; a prediction field determination module, in communication with the input, for determining the prediction field based upon the first field, the prediction field providing what the image data 20 corresponding to the second field would be if there were a substantial lack of motion between the fields; and a field recovery module, in communication with the prediction field determination module, for reconstructing the second field by adding the error field to the prediction field. 12. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: means for receiving predicted frame data including image data corresponding to the first field and to an error field, the error field corresponding to the difference between the second field and a prediction field of the second field; means for determining the prediction field based upon the first field, the prediction field providing what the image data corresponding to the second field would be if there were a substantial lack of motion between the fields; and means for reconstructing the second field by adding the error field to the prediction field. 13. A method for processing an image signal having frames with a first field and a second field, the method comprising: receiving image data corresponding to the first field and the second field, the first field and the second field being interlaced; obtaining a low frequency field for each frame using the first and second fields; obtaining a high frequency field for each frame using the first and second fields; and producing frame data, each frame including the low frequency field and the high frequency field, the low frequency field and the high frequency field being non-interlaced. 14. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: 21 an input, for receiving image data corresponding to the first field .and the second field, the first field and the second field being interlaced; a vertical transform module, in communication with the input, for obtaining a low frequency field for each frame using the first and second fields, and for obtaining a high frequency field for each frame using the first and second fields; and a signal merging module, in communication with the vertical transform module, for producing frame data, each frame including the low frequency field and the high frequency field, the low frequency field and the high frequency field being non-interlaced. 15. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: means for receiving image data corresponding to the first field and the second field, the first field and the second field being interlaced; means for obtaining a low frequency field for each frame using the first and second fields; means for obtaining a high frequency field for each frame using the first and second fields; and means for producing frame data, each frame including the low frequency field and the high frequency field, the low frequency field and the high frequency field being non-interlaced. 16. A method for processing an image signal having frames with a first field and a second field, the method comprising: receiving image data corresponding to the first field and the second field, wherein the second field is designated to be a reference field; determining a prediction field from the reference field, the prediction field providing what the image data corresponding to the first field would be if there were a substantial lack of motion between the fields; 22 determining an error field using the difference between the first field and the prediction field; and producing predicted frame data, the predicted frame data including the second field and the error field, the second field and the error field being non-interlaced. 17. An apparatus for processing an image signal having frames with a first field and a second field, the apparatus comprising: an input, for receiving image data corresponding to the first field and the second field, wherein the second field is designated to be a reference field; a prediction field determination module, in communication with the • input, for determining a prediction field from the reference field, the prediction field providing what the image data corresponding to the first field would be if there were a substantial lack of motion between the fields; an error field determination module, in communication with the prediction field determination module, for determining an error field using the difference between the first field and the prediction field; and a signal merging module, in communication with the error field determination module, for producing predicted frame data, the predicted frame data including the second field and the error field, the second field and the error field being non-interlaced. 23

Inventors: GOERTZEN KENBE, GOERTZEN, KENBE
Applicants: QUVIS INC, QUVIS, INC.
Application year: 1999
Main classification: G06K9
IPC codes: G06T9, H04N7