CN105844677A - Adaptive filtering encoding device - Google Patents
Adaptive filtering encoding device Download PDFInfo
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- CN105844677A CN105844677A CN201610156931.XA CN201610156931A CN105844677A CN 105844677 A CN105844677 A CN 105844677A CN 201610156931 A CN201610156931 A CN 201610156931A CN 105844677 A CN105844677 A CN 105844677A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
- G06T9/004—Predictors, e.g. intraframe, interframe coding
Abstract
The invention discloses an adaptive filtering encoding device, comprising a template matching module, an intra-frame prediction module, a model construction module, a prediction value calculation module, a gray value calculation module, an error value prediction module and an encoding module. The template matching module is used for obtaining a template of a current encoding block, searching for at least two matching templates according to template matching, and obtaining the prediction of the current encoding block according to the matching templates; the intra-frame prediction module is used for performing intra-frame mode prediction on the frame after filtering processing, performing intra-frame prediction on a prediction block of the current encoding block, and obtaining the pixel value of the intra-frame prediction of each pixel in the prediction block; the model construction module is used for constructing a prediction model of the pixel values on the basis of adaptive filtering; the prediction value calculation module is used for calculating the prediction value of a sample point according to the prediction model; the gray value calculation module is used for calculating the gray value of a pixel point according to the prediction value; the error value prediction module is used for calculating the error value according to the pixel point gray value; and the encoding module is used for encoding an image according to the error value. The adaptive filtering encoding device can effectively reduce the residual error after the intra-frame prediction.
Description
Technical field
The invention belongs to image technique field, specifically, relate to a kind of adaptive-filtering code device.
Background technology
In method for compressing image, picture is divided into graphics processing unit, to encode image.
Then, by using inter prediction or infra-frame prediction that each macro block is encoded.
The block that existing coded system is required to when generating final predictive value produce its prediction is adjacent
Pixel is fixed the filter filtering of tap and processes.Owing to video signal has non-stationary, fix and take out
The wave filter of head is difficult to meet the change of picture material, and after causing having carried out filtering, the residual error of infra-frame prediction depends on
The biggest, it is difficult to compression, become the technical barrier of intraframe predictive coding.
Summary of the invention
In view of this, the technical problem to be solved is, is filtered in rear frame in prior art
The residual error ratio of prediction is bigger, it is difficult to the problem of compression.
In order to solve above-mentioned technical problem, the invention discloses a kind of adaptive-filtering code device, including:
Stencil matching module, for obtaining the template of present encoding block, and searches for according to described template matching
At least two matching template, obtains the prediction of present encoding block according to described matching template；
Intra-framed prediction module, for needing the intra prediction mode that processes after filtering, to described currently
The prediction block of encoding block carries out infra-frame prediction, it is thus achieved that each pixel infra-frame prediction in described prediction block
Pixel value；
Model construction module, for building the forecast model based on adaptive-filtering of described pixel value；
Predictor calculation module, for calculating the predictive value of sample point according to described forecast model；
Gray value computing module, for according to described predictor calculation pixel gray value；
Error amount prediction module, for calculating error amount according to described pixel gray value；
Coding module, for encoding image according to described error amount.
Further, described forecast model be f (x, y)=0.5 (x, y-1)+0.5f (and x-1, y).
Further, described error amount calculation is eN=xN-x′N, eNFor error amount, xNFor tNTime
The luminance samples value carved, x'NFor predictive value.
Further, described forecast model is previous value prediction model.
Further, described forecast model is one-dimensional prediction model.
Further, described forecast model is two-dimensional prediction model.
Further, described forecast model is three-dimensional prediction model.
Compared with prior art, the present invention can obtain and include techniques below effect:
(1) present invention is based on adaptive filter algorithm, in conjunction with the feature of picture signal, changes
It is applied to after entering, in the middle of compression of images prediction, obtain specific algorithm, shown by emulation, it was predicted that mean square error
Difference (MSE) and error image comentropy are superior to JPEG-LS standard and the predictor of CALIC algorithm,
There is more preferable prediction effect.
(2) residual error after the present invention can also effectively reduce infra-frame prediction, in the case of identical code check,
The picture quality of decoding significantly improves.Certainly, the arbitrary product implementing the present invention must be not necessarily required to simultaneously
Reach all the above technique effect.
Accompanying drawing explanation
Accompanying drawing described herein is used for providing a further understanding of the present invention, constitutes of the present invention
Point, the schematic description and description of the present invention is used for explaining the present invention, is not intended that the present invention's
Improper restriction.In the accompanying drawings:
Fig. 1 show the module map of the embodiment of the present invention a kind of adaptive-filtering code device.
Detailed description of the invention
Embodiments of the present invention are described in detail, thereby to the present invention below in conjunction with drawings and Examples
How application technology means solve technical problem and reach the process that realizes of technology effect and can fully understand
And implement according to this.
Fig. 1 show the module map of the embodiment of the present invention a kind of adaptive-filtering code device.
The adaptive-filtering code device that the embodiment of the present invention provides, including: in stencil matching module, frame
Prediction module, model construction module, predictor calculation module, gray value computing module, error amount are predicted
Module, and coding module.
Stencil matching module, for obtaining the template of present encoding block, and searches for according to described template matching
At least two matching template, obtains the prediction of present encoding block according to described matching template.
In the present embodiment, the object of known form can be detected in the picture, use this object
Shape template (or window) and images match, detect object image under certain criterion of agreement.
The present embodiment can detect upper lines, curve, pattern etc. in image.
Intra-framed prediction module, for needing the intra prediction mode that processes after filtering, to described currently
The prediction block of encoding block carries out infra-frame prediction, it is thus achieved that each pixel infra-frame prediction in described prediction block
Pixel value.
In the present embodiment, in HEVC, the intra-frame prediction method that can use for depth map
35 kinds of patterns, and the MPM pattern obtained by the left side and the right adjacent block be all by calculate RDO
Process carries out judging.
Specifically, a total of four steps of the present embodiment obtain optimum depth prediction pattern:
First, by RDM calculates the SATD of each intra prediction mode then select one thick
Slightly set of modes.The block of 4*4,8*8 is 8 kinds, and the block of 16*16,32*32 is 3 kinds；
Then, during the pattern obtained by MPM joins coarse mode set；
Secondly, the pattern selected by 4 kinds of DMM patterns is also added in candidate collection.
Finally, the model prediction of optimum is obtained by calculating RDcost.
It addition, because texture image needs the selection using SATD to carry out pattern, depth map and texture are again
There is certain pixel column, so using SATD pattern to reduce unnecessary WEDGELET pattern.This
The detailed process of embodiment is as follows:
Firstly, because the line of segmentation block can correspond to the angle of one or two HEVC on direction
Pattern, so being angle mode by all of Wedgelet pattern classification.
Then, the angle mode of the SATD having minimum is selected.Then SSE is used to calculate each angle
Pattern optimum in Wedgelet mode subset corresponding to degree.
Finally, the angle mode elected, and the optimum pattern in subset and other 3 kinds of DMM
Pattern selects a kind of pattern of optimum.
Model construction module, for building the forecast model based on adaptive-filtering of described pixel value.This
In embodiment, described forecast model be f (x, y)=0.5 (x, y-1)+0.5f (and x-1, y).In other embodiments,
Described forecast model can also be two dimension for previous value prediction model, one-dimensional prediction model, described forecast model
Forecast model, or three-dimensional prediction model.
The present embodiment can use least mean square algorithm by object function is carried out suitable adjustment, it is achieved
Adaptive effect.The present embodiment mainly utilizes least mean square algorithm complexity, receipts in Stationary Random Environments
Converge to the characteristics such as wiener solution to holding back property, its average unbiased.In Stationary Random Environments, accurate according to mean square error
Then optimal linear filtering device.Assume the stationary random signal that signal is zero-mean, adaptive-filtering can be designed
Device is to be made up of linear combiner.The present embodiment can process one dimensional image, the image of two dimension, Yi Jisan
Dimension image
Predictor calculation module, for calculating the predictive value of sample point according to described forecast model.
Gray value computing module, for according to described predictor calculation pixel gray value.
Error amount prediction module, for calculating error amount according to described pixel gray value.In the present embodiment,
Described error amount calculation is eN=xN-x′N, eNFor error amount, xNFor tNThe luminance samples value in moment,
x′NFor predictive value.
Coding module, for encoding image according to described error amount.
The present embodiment can by picture coding be MPEG4, H.263, H.264, the form such as M-JPEG,
This is not construed as limiting by the present invention.
Compared with prior art, the present invention can obtain and include techniques below effect:
(1) present invention is based on adaptive filter algorithm, in conjunction with the feature of picture signal, changes
It is applied to after entering, in the middle of compression of images prediction, obtain specific algorithm, shown by emulation, it was predicted that mean square error
Difference (MSE) and error image comentropy are superior to JPEG-LS standard and the predictor of CALIC algorithm,
There is more preferable prediction effect.
(2) residual error after the present invention can also effectively reduce infra-frame prediction, in the case of identical code check,
The picture quality of decoding significantly improves.
Also, it should be noted term " includes ", " comprising " or its any other variant are intended to non-
Comprising of exclusiveness, so that include that the commodity of a series of key element or system not only include that those are wanted
Element, but also include other key elements being not expressly set out, or also include for this commodity or be
Unite intrinsic key element.In the case of there is no more restriction, statement " including ... " limit
Key element, it is not excluded that there is also other identical element in the commodity including described key element or system.
Described above illustrate and describes some preferred embodiments of the present invention, but as previously mentioned, it should reason
Solve the present invention and be not limited to form disclosed herein, be not to be taken as the eliminating to other embodiments,
And can be used for various other combination, amendment and environment, and can in invention contemplated scope described herein,
It is modified by above-mentioned teaching or the technology of association area or knowledge.And those skilled in the art are carried out changes
Move and change is without departing from the spirit and scope of the present invention, the most all should be in the protection of claims of the present invention
In the range of.
Claims (7)
1. an adaptive-filtering code device, it is characterised in that including:
Stencil matching module, for obtaining the template of present encoding block, and searches for according to described template matching
At least two matching template, obtains the prediction of present encoding block according to described matching template；
Intra-framed prediction module, for needing the intra prediction mode that processes after filtering, to described currently
The prediction block of encoding block carries out infra-frame prediction, it is thus achieved that each pixel infra-frame prediction in described prediction block
Pixel value；
Model construction module, for building the forecast model based on adaptive-filtering of described pixel value；
Predictor calculation module, for calculating the predictive value of sample point according to described forecast model；
Gray value computing module, for according to described predictor calculation pixel gray value；
Error amount prediction module, for calculating error amount according to described pixel gray value；
Coding module, for encoding image according to described error amount.
2. adaptive-filtering code device as claimed in claim 1, it is characterised in that described prediction
Model be f (x, y)=0.5 (x, y-1)+0.5f (and x-1, y).
3. adaptive-filtering code device as claimed in claim 2, it is characterised in that described error
Value calculation is eN=xN-x′N, eNFor error amount, xNFor tNThe luminance samples value in moment, x 'NFor
Predictive value.
4. adaptive-filtering code device as claimed in claim 1, it is characterised in that described prediction
Model is previous value prediction model.
5. adaptive-filtering code device as claimed in claim 1, it is characterised in that described prediction
Model is one-dimensional prediction model.
6. adaptive-filtering code device as claimed in claim 1, it is characterised in that described prediction
Model is two-dimensional prediction model.
7. adaptive-filtering code device as claimed in claim 1, it is characterised in that described prediction
Model is three-dimensional prediction model.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1767654A (en) * | 2004-10-26 | 2006-05-03 | 日本电气株式会社 | The computer program of image encoder and method thereof, image encoder and portable terminal |
| CN101715135A (en) * | 2009-09-30 | 2010-05-26 | 武汉大学 | Template matching based method for encoding self-adaption intra-frame prediction filtering |
| CN102378009A (en) * | 2011-11-14 | 2012-03-14 | 清华大学深圳研究生院 | Fast algorithm for estimating optical parallax |
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2016
- 2016-03-18 CN CN201610156931.XA patent/CN105844677A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1767654A (en) * | 2004-10-26 | 2006-05-03 | 日本电气株式会社 | The computer program of image encoder and method thereof, image encoder and portable terminal |
| US7933334B2 (en) * | 2004-10-26 | 2011-04-26 | Nec Corporation | Image encoder and method thereof, computer program of image encoder, and mobile terminal |
| CN101715135A (en) * | 2009-09-30 | 2010-05-26 | 武汉大学 | Template matching based method for encoding self-adaption intra-frame prediction filtering |
| CN102378009A (en) * | 2011-11-14 | 2012-03-14 | 清华大学深圳研究生院 | Fast algorithm for estimating optical parallax |
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