|Numéro de publication||US7675573 B2|
|Type de publication||Octroi|
|Numéro de demande||US 11/332,841|
|Date de publication||9 mars 2010|
|Date de priorité||18 févr. 2005|
|État de paiement des frais||Payé|
|Autre référence de publication||EP1694066A1, US20060187345|
|Numéro de publication||11332841, 332841, US 7675573 B2, US 7675573B2, US-B2-7675573, US7675573 B2, US7675573B2|
|Inventeurs||Eduardo Rogelio Corral Soto, Peter Swartz, Andrew Mackinnon|
|Cessionnaire d'origine||Genesis Microchip Inc.|
|Exporter la citation||BiBTeX, EndNote, RefMan|
|Citations de brevets (13), Citations hors brevets (7), Classifications (7), Événements juridiques (2)|
|Liens externes: USPTO, Cession USPTO, Espacenet|
This patent application is a Continuation in Part of U.S. patent application Ser. No. 11/143,510 filed on Jun. 1, 2005 now U.S. Pat. No. 7,471,336, entitled that takes priority under 35 U.S.C. 119(e) to U.S. Provisional Patent Application No. 60/654,263 filed on Feb. 18, 2005 entitled “GLOBAL MOTION ADAPTIVE SYSTEM WITH MOTION VALUES CORRECTION WITH RESPECT TO LUMINANCE LEVEL” that is incorporated by reference in its entirety.
The invention pertains in general to motion adaptive deinterlacing, and in particular to systems and methods for adaptively adjusting local motion thresholds according to global motion indicators in order to reduce scintillation and feathering artifacts.
Interlaced video signals comprise two video fields, one for the odd lines and one for the even lines of an image. This is due to the image capture process, wherein the camera outputs the odd lines at one instant in time and the even lines slightly later. This creates a temporal shift between the odd and even lines of the image, which needs to be addressed in frame based processing systems. A deinterlacing process generally attempts to overcome this problem by assembling a clean frame from the two fields.
Since the temporal shift between the two fields introduce feathering and scintillation artifacts, motion adaptive deinterlacing (MADI) techniques have been proposed in order to reduce such artifacts. Some MADI techniques use local motion threshold values that can be adjusted manually in order to improve the performance of the de-interlacer on a specific problematic video sequence, albeit possibly at the cost of sacrificing the performance (and re-introducing de-interlacing artifacts) in other video sequences.
Therefore, instead of manually adjusting the MADI thresholds in order to “Pass” a specific video sequence, it is desirable to develop a new adaptive system that adjusts the local MADI thresholds automatically and adaptively.
Disclosed are global-adaptive deinterlacing systems and methods for reducing scintillation and feathering artifacts. MADI local motion quantization thresholds are adaptively adjusted according to the amount of global motion present in the video sequence, thereby minimizing scintillation artifacts (generally present in low motion images) and feathering artifacts (generally present in high motion images) when deinterlacing the fields. A set of global motion “scenarios” are defined for the purpose of classifying fields, and a number of global motion indicators are used to detect on a field-by-field basis different global motion scenarios. The global motion indicators are corrected to reduce Luma dependencies, thereby improving reliability and robustness. Depending on the global motion scenario of a field, the local motion thresholds are adaptively adjusted. The adaptive adjustment of quantization thresholds are optionally also applied to temporal noise reduction and cross-color suppression sub-systems.
The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
Reference will now be made in detail to a particular embodiment of the invention, examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with the particular embodiments, it will be understood that it is not intended to limit the invention to the described embodiments. To the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims.
Motion Adaptive Deinterlacing and Local Motion Quantization Thresholds
An interlaced video signal comprises odd fields (lines 1, 3, 5, . . . ) and even fields (lines 2, 4, 6, . . . ). A deinterlacing video processing system produces a progressive video output signal from an interlaced video input signal for viewing on a progressive display device. Instead of performing simple fields merging (i.e. static mesh) to deinterlace the input video, a combination of vertical interpolation and temporal interpolation is performed in order to obtain a high quality deinterlaced image frame which has a minimum of flickering artifacts in the static areas and a minimum of feathering artifacts in the moving areas. In order to better achieve this goal, local motion (such as on a pixel-by-pixel basis) in the input sequence can be estimated in order to separately process the static and the moving portions of the image depending upon the presence and level of local motion in the vicinity of each pixel. This is referred to as motion adaptive deinterlacing (MADI), and two main tasks of such a MADI system are:
1. Motion detection, comprising detecting the level of local motion for each pixel and/or its neighborhood; and
2. Deinterlacing, thereby producing a progressive frame.
In order to detect the presence of local motion in the input video sequence, two fields of the same polarity (i.e. even and even, or odd and odd) are used by the MADI system in order to compute the value differences (i.e. temporal variation) between each two pixels having the same coordinates in the two fields. In addition, differences between pixel values of two adjacent fields in the vertical direction may be computed in order to recognize the presence of vertical motion. The MADI system then estimates local motion values for each pixel based on the obtained temporal variation, vertical variation and optionally global noise present in the video signal. Once estimated, the local motion values are quantized into a number of levels as indicated by a set of MADI local motion quantization thresholds, which define a set of local motion ranges. The pixels are then deinterlaced by a set of available methods according to the quantized local motion values.
Global-Adaptive Deinterlacing System
While a MADI system as described above does reduce deinterlacing artifacts, scintillation and feathering artifacts are still present in the final deinterlaced sequence. Disclosed herein are global-adaptive deinterlacing systems and methods for reduce scintillation and feathering artifacts by adaptively adjusting the MADI local motion quantization thresholds according to the amount of global motion present in the video sequence. A set of global motion “scenarios” are defined for the purpose of classifying sequences, and a number of global motion indicators are used to detect on a field-by-field basis different global motion scenarios. Depending on the global motion scenario of a field, the local motion thresholds are dynamically adjusted, thereby minimizing scintillation artifacts (generally present in low motion images) and feathering artifacts (generally present in high motion images) when deinterlacing the field.
Global Motion Indicators: R and S Signals
Two signals, hereinafter referred to as R and S signals, are used as initial indicators of the amount of global motion present in the input image. These signals may be generated by a Film Mode detection block of the de-interlacer system, or they may be separately computed. The R and S signals are defined as functions of the incoming fields as follows:
c = curr_field
Luma values of the current
field in the interlaced video
signal (can be even or odd)
p = prev_field
Luma values of the previous
field (in time) in the
interlaced video signal
(when c is even p is odd,
and vice versa).
p−1 = field previous to p
Luma values of the field
previous to p (in time).
R = c − p−1
and conversion of result
to a scalar R = sum(c − p−1).
S = c − p
and conversion of result
to a scalar S = sum(c − p).
Note that when the interlaced video signal comprises little global motion, c and p are close in value and their difference is small. Furthermore, when an object moves from an odd field to an even field (or vice versa), the spatial shift causes a corresponding increase in the result of the subtractions. An example image from a sample video sequence is shown in
Correcting the R and S Signals
Since the R and S global motion indicators are obtained by performing Luma subtractions between different video fields, the signals are dependent on the Luma levels. For example, if a specific video sequence comprising objects moving at a fixed speed is played with two different Luma levels (i.e. two different brightness levels), the two obtained sets of R and S values corresponding to each Luma level will be different.
When the maximum Luma levels in the incoming video fields vary, the magnitude of the R and S signals are altered (scaled) by a factor ƒ(Ymax). Therefore, from this moment we will refer to the R and S signals as the uncorrected Suncorr and Runcorr signals.
S uncorr =S·ƒ(Y max)
R uncorr =R·ƒ(Y max)
where Ymax represents the maximum Luma value in the video field. The function ƒ is an exponential function as the ones shown in
The Luma dependency problem affects the performance of the deinterlacer as illustrated by the examples of
In order to remove or at least reduce the dependency on the Luma level, an inverse function
is defined for multiplication by the Runcorr and Suncorr values as follows:
Where the Scorr and Rcorr corrected values represent acceptable approximations of the desired R and S indicators.
By way of example, the inverse function g(Ymax) may be defined as a 256-entry (for an 8-bit system) 8.8 Fixed-Point format look-up table (for example implemented in firmware or hardware).
In these correction functions LUT, an entry is selected according to the maximum Luma level (index) detected in the field. Then the entry is multiplied by the Suncorr and Runcorr values. In the shown correction functions the entries corresponding to Luma values lower than 128 (50%) are clipped in order to avoid over-correction caused by a division by zero. For Luma values equal or higher than 235 (ITU???-601 standard) the correction value is clipped to 1.
In order to correct the pairs of Suncorr and Runcorr values for a given field, the maximum Luma level of the field is determined. The maximum Luma value can be directly computed, or may simply be available from the deinterlacing system. For example, a MADI chip may have a register making available the maximum Luma value detected in the current field. This value is then used as an index to a correction look-up table in order to properly select a correction factor which will be multiplied with the Suncorr and Runcorr values to obtain the Scorr and Rcorr values that will be used as the corrected global motion indicators.
This avoids the reduction of the global motion magnitude values and hence generates a reliable (nearly-constant) pair of Scorr and Rcorr values (for the range of Luma levels 50-100%). Thereby improving de-interlacer robustness by retaining the high performance of the deinterlacer in dark scenes.
A set of motion scenarios is defined in order to classify fields depending on the level of global motion and presence of vertical motion pattern. The following scenarios are used:
Low motion scenario: Indicating still images or very low global motion images.
Medium motion scenario: Indicating medium global motion images.
High motion scenario: Indicating high global motion images.
Vertical motion scenario: Indicating images with vertical global motion pattern.
Given an image in a sequence, a scenario is determined based on the Rcorr and Scorr signals. The scenario indicates appropriate adjustments to the local motion thresholds according to the amount of global motion and/or the presence of vertical motion in the image. By way of example, the following definitions have been found to work well:
Scorr and Rcorr values below the threshold value of Tlow=3 (higher 16 bits of a 32-bit word) indicating a low global motion scenario, Scorr and Rcorr values between the Tlow=3 and Thigh=4800 indicating a medium global motion scenario, and Scorr and Rcorr values above Thigh=4800 indicating a high global motion scenario.
Adjusting Quantizer Threshold Values of a Motion Adaptive De-Interlacer
Generally, the local motion value of a specific pixel in a given field are determined by computing a function of pixel Luma and/or Chroma,
involving the specific pixel (and its neighbors) contained in the current, previous and previous−1 fields.
Because of cost and computational overhead reasons, the obtained local motion value for the analyzed pixel is quantized hence reducing its resolution.
If the thresholds in the quantizer are adjustable, then the distribution of local motion codes can be adjusted accordingly.
Therefore, adjusting the quantizer threshold values essentially redistributes the sensitivity of the quantizer. If the quantizer thresholds are set to a relatively low value, then the Motion Adaptive De-interlacer will treat most of the pixels as if they had high local motion. Consequently, slow moving objects will exhibit scintillation artifacts.
On the other hand, if the quantizer thresholds are set to a relatively high value, then the Motion Adaptive De-interlacer will treat most of the pixels as if they had low local motion. Consequently, fast moving objects will exhibit feathering artifacts.
As described above, the present invention adjusts the local motion quantization thresholds according to the amount of global motion. As an example, the local motion values may be originally represented by 8-bit numbers and subsequently quantized by a 2-bit quantizer into four levels indicated by a set of three local motion quantization thresholds MADI_QUANT_THRESH0, MADI_QUANT_THRESH1 and MADI_QUANT_THRESH2, as follows:
Local motion level 0: local motion<MADI_QUANT_THRESH0
Local motion level 1: MADI_QUANT_THRESH0≦local motion<MADI_QUANT_THRESH1
Local motion level 2: MADI_QUANT_THRESH1≦local motion<MADI_QUANT_THRESH2
Local motion level 2: MADI_QUANT_THRESH2≦local motion
Thus, in this example, a quantized local motion value obtained for a pixel indicates which one of four available deinterlacing methods will be used to deinterlace the pixel.
Feathering artifacts occur when the pixels and lines of a moving object are wrongly deinterlaced by the use of the “fields pairing” technique. The effect is a misalignment of the moving object pixels visible as horizontal lines. This problem can be improved by lowering the values of the local motion thresholds. Scintillation artifacts occur when the pixels and lines of a static object are wrongly deinterlaced by the use of the “spatial processing” (vertical filtering) technique. The effect is a flickering artifact on the static object pixels. This problem can be improved by raising the values of the local motion thresholds.
The thresholds start out with a set of “default” values. By way of example, default values of approximately MADI_QUANT_THRESH0=6, MADI_QUANT_THRESH1=8 and MADI_QUANT_THRESH2=15 have been found to work well. In order to deinterlace an incoming field, first a global motion scenario is identified for the field as described above. If the field exhibits a medium motion scenario, the default thresholds remain in place (or are reverted to) and used by the quantizer to determine local motion values for the pixels in the field and choose a deinterlacing method accordingly. However, if the field comprises a low motion scenario, the probability of scintillation artifacts to occur gets increased. In order to prevent the presence of these artifacts, the local motion regions in the quantizer are re-distributed accordingly by raising the local motion thresholds.
By way of example, an adjustment of approximately MADI_QUANT_THRESH0=13, MADI_QUANT_THRESH1=14 and MADI_QUANT_THRESH2=15 has been found to work well.
On the other hand, if the field comprises a high motion scenario, the thresholds are lowered accordingly. By way of example, an adjustment of approximately MADI_QUANT_THRESH0=4, MADI_QUANT_THRESH1=5 and MADI_QUANT_THRESH2=15 has been found to work well. As a result, presence of global motion appropriately affects the local motion regions used by the deinterlacer in order to reduce artifacts such as scintillation and feathering.
Vertical Motion Pattern Detection
Vertical motion may cause artifacts during a medium motion scenario. Vertical global motion is detected in a number of ways. One approach makes use of the Scorr signal, as shown in the graph of
Another approach to vertical motion detection utilizes a vertical motion detector element that detects vertical global motion by way of a four stage process. First, vertical motion of individual pixels is detected. These motion values are used to determine the vertical motion of tiles which divide the input field. Last, the motion values of the tiles in a field are used to determine whether that entire field is judged to be in vertical motion.
The pixel vertical motion is calculated by comparing the top- and bottom-most pixel in the current field with the pixels in the previous field of opposite parity. For example, with an ODD current field, if tap C show high correlation to either tap E and/or tap B, the pixel is said to have downward motion. To prevent motion aliasing, detection of downward motion is predicated on the pixel in the corresponding location in the previous field of the same parity being uncorrelated with the tap in the current field (for example, C and C′ must be uncorrelated). Correlation can be measured with either a simple absolute difference or via more elaborate correlation functions. Pixels in vertical motion then cause a tile counter to be either incremented or decremented based on their direction of motion.
The taps in the current field are divided spatially into rectangular tiles. With each tile is associated a counter, which increments of decrements according to the pixel motion calculated above. The tile counter provides a measure of the overall motion of pixels within the tiles: if the tile counter is positive, the pixels are, on average, moving upwards, and if negative, downwards. The counter value is compared with a threshold to provide noise immunity; if the threshold is exceeded, the tile is judged to be in vertical motion. A field vertical motion counter is incremented or decremented based on the direction of the tile motion.
Next, the field motion counter is compared with another threshold to determine if the entire field has vertical motion. This threshold is adaptive based on attributes of the input field, such as parity. This creates a two bit output signal which indicates if the field is in vertical motion, and if so, the direction of motion, up or down.
Finally, a history of the vertical motion is kept over several fields. If this vertical motion is consistent and in the same direction over several fields, a high degree of confidence that vertical motion is real exists. In this case a final one-bit output signal indicates that the input sequence contains vertical motion. This output signal uses hysteresis to prevent noise from causing quick successive changes in the detected vertical motion.
Temporal Noise Reduction
Optionally, the deinterlacer may comprise a temporal noise reduction (TNR) component, having a separate local motion values quantizer for increased flexibility. In such an embodiment, an initial noise measurement may be obtained from a sub-system of the deinterlacer, wherein such a sub-system may comprise a noise meter and optionally some digital filtering to produce a reliable noise measurement. This noise measurement may then be combined with the global motion indicators Scorr and Rcorr to automatically adjust both the amount of noise reduction and the local motion thresholds according to the measured noise and global motion. The objective of using the global motion values is to avoid “ghosting” artifacts (blurring) on moving objects that occur when the amount of noise reduction is relatively high in the high-motion objects. The objective of using the noise measurements is to adjust the amount of noise reduction according to the noise present in the image.
Cross Color Suppression
Optionally, the deinterlacer may comprise a cross color suppression (CCS) component, having a separate local motion values quantizer for increased flexibility. In such an embodiment, the quantizer thresholds can be adjusted based on the global motion indicators Scorr and Rcorr in order to reduce blurring of colors and ghosting artifacts in video sequences involving motion.
Foregoing described embodiments of the invention are provided as illustrations and descriptions. They are not intended to limit the invention to precise form described. Other variations and embodiments are possible in light of above teachings, such as implementing the described embodiments in hardware or software.
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|Classification aux États-Unis||348/452|
|Classification coopérative||H04N7/0132, H04N7/0137, H04N5/144, H04N7/012|
|2 mars 2006||AS||Assignment|
Owner name: GENESIS MICROCHIP INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:SOTO, EDUARDO ROGELIO CORRAL;SWARTZ, PETER;MACKINNON, ANDREW;REEL/FRAME:017304/0125;SIGNING DATES FROM 20060206 TO 20060216
Owner name: GENESIS MICROCHIP INC.,CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:SOTO, EDUARDO ROGELIO CORRAL;SWARTZ, PETER;MACKINNON, ANDREW;SIGNING DATES FROM 20060206 TO 20060216;REEL/FRAME:017304/0125
|11 mars 2013||FPAY||Fee payment|
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