CN108337509A - The noise-reduction method and device of block distortion - Google Patents

The noise-reduction method and device of block distortion Download PDF

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Publication number
CN108337509A
CN108337509A CN201810303006.4A CN201810303006A CN108337509A CN 108337509 A CN108337509 A CN 108337509A CN 201810303006 A CN201810303006 A CN 201810303006A CN 108337509 A CN108337509 A CN 108337509A
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Prior art keywords
block
pixel
noise
boundary
pixel value
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谢将相
郭李军
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Beijing Huimor Technology Co Ltd
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Beijing Huimor Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/117—Filters, e.g. for pre-processing or post-processing
    • 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
    • H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
    • H04N19/86—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving reduction of coding artifacts, e.g. of blockiness

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Image Processing (AREA)
  • Compression Of Band Width Or Redundancy In Fax (AREA)

Abstract

The invention discloses a kind of noise-reduction method of block distortion and device, which includes the following steps：1) according to the absolute difference and pixel value range of border side pixel in the block of pixels of input, analysis obtains the block distortion type of border side pixel in the block of pixels；2) the noise reduction filtering algorithm that adaptation is chosen according to the block size of the block distortion type of boundaries on either side pixel in block of pixels and pixel is filtered pixel in block of pixels.The present invention classifies to the block distortion of input pixel boundary both sides, and the noise reduction filtering algorithm that selection is suitable for different blocky noise types is filtered the pixel of boundaries on either side, improves the noise reduction of block distortion, the image after noise reduction shows clear.

Description

The noise-reduction method and device of block distortion
Technical field
The invention belongs to technical field of image processing more particularly to the noise-reduction methods and device of a kind of picture noise.
Background technology
The video content of numerous pressure sources, for example, MPEG-2/DVD, MPEG-4, H.263, H.264, VC-1, AVS and The video source bit rate of the formats such as RMVB is low, and this compression video is shown and will appear various compression artefacts, including block effect Answer either blocky noise, ring or mosquito formula noise etc..When being shown on large-screen display equipment, problem of dtmf distortion DTMF is especially apparent.
Currently, reducing, blocky, there are many general noise reduction algorithm of mosquito formula noise, but the image after noise reduction process can introduce other Quality degradation, for example, it is fuzzy the problems such as.
Invention content
In view of the problems of the existing technology, after the purpose of the present invention is to provide a kind of raising noise reduction and noise reduction The noise-reduction method and device of the mosquito noise of video display quality.
To achieve the above object, the noise-reduction method of picture noise of the invention, includes the following steps：
1) determine that the pseudo- block threshold value of macro block and block gray scale dynamic range determine the block threshold value of macro block in the decoding image of input；
2) according to the comparison result of the pixel value of pixel in macro block and the block threshold value of macro block, two of pixel value in macro block are obtained Member index；
3) pixel to be filtered in macro block is determined according to the binary index of pixel value in macro block；
4) pixel to be filtered is filtered using scheduled filtering algorithm.
Further, determine that the block threshold value of macro block and block gray scale dynamic range include according to the decoding image of input：
Block threshold value thr=(max+min+1)/2,
Block gray scale dynamic range range=max-min,
Wherein max indicates that the max pixel value of whole pixels in current block, min indicate the minimum of whole pixels in current block Pixel value.
Further, according to the comparison result of the pixel value of pixel in macro block and the block threshold value of macro block, pixel in macro block is obtained The binary of value indexes：
Conducive to formulaObtain the binary index of pixel value in macro block, wherein rec (h, v) is the pixel value of coordinate (h, v), wherein h, v=0,1,2 ..., 7, bin (h, v) is the binary rope of pixel value in macro block Draw.
Further, determine that pixel to be filtered in macro block includes according to the binary index of pixel value in macro block：
When binary index in 3 × 3 windows is all identical, corresponding pixel is chosen to be to pixel to be filtered.
Further, using scheduled filtering algorithm to the pixel to be filtered be filtered including：
Conducive to formulaTo the pixel to be filtered It being filtered, wherein coef (i, j) indicates that filtration coefficient, rec (h+i, v+j) they are the pixel value of coordinate (h+i, v+j), Flt'(h, v) indicate Filtered Picture element pixel value.
Further, the noise-reduction method further includes：
5) intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, obtained final Noise reduction pixel.
Further, the noise-reduction method further includes：
6) selectivity output input pixel or the final noise reduction pixel.
Further, the advanced row block noise filtering processing before carrying out above-mentioned mosquito noise and being filtered.
Further, the block noise be filtered including：
1) according to the absolute difference and pixel value range of border side pixel in the block of pixels of input, analysis obtains the pixel The block distortion type of border side pixel in block；
2) noise reduction of adaptation is chosen according to the block size of the block distortion type of boundaries on either side pixel in block of pixels and pixel Filtering algorithm is filtered pixel in block of pixels.
Further, the block noise, which is filtered, further includes：
3) intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, obtained final Noise reduction pixel.
Further, the block noise, which is filtered, further includes：
4) selectivity output input pixel or the final noise reduction pixel.
Further, further include before the step 1) that the block noise is filtered：
Calculate the absolute difference and pixel value range of border side pixel in the block of pixels of input.
Further, the block distortion type of the pixel includes that no block noise, real border, block noise be apparent and block noise Unobvious.
Further, the block size of pixel is 8 and when the block distortion type of boundaries on either side is that the block noise is apparent, choosing The noise reduction filtering algorithm taken is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△/8)
f2=CLIP_0_255 (p2+2△/8)
f3=CLIP_0_255 (p3+△/8)
Wherein, p1、p2、p3Indicate boundary side pixel value to be filtered, p0Indicate the pixel that the boundary other side does not filter Value, f1、f2、f3Indicate the pixel value of boundary side filtering output.
Further, the block size of pixel is 8 and the block distortion type of boundary side is that block noise is apparent, the boundary other side Block distortion type be block noise unobvious when, the noise reduction filtering algorithm of selection is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+△/2)
f2=CLIP_0_255 (p2+△/8)
f0=CLIP_0_255 (p0-△/8)
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p0Indicate boundary other side pixel value to be filtered, f1、f2Indicate the pixel value of boundary side filtering output, f0Indicate the pixel value of boundary other side filtering output.
Further, it when the block size of pixel is block noise unobvious for the block distortion type of 8 and boundaries on either side, chooses Noise reduction filtering algorithm it is as follows：
f1=(p0+2×p1+p2+2)>>2
f2=(p1+4×p2+3×p3+4)>>3
f3=(3 × p2+4×p3+p4+4)>>3
f4=(p3+2×p4+p5+2)>>2
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p3、p4Indicate boundary other side pixel to be filtered Value, p0Indicate the pixel value that boundary side does not filter, p5Indicate the pixel value that the boundary other side does not filter, f1、f2Indicate boundary one The pixel value of side filtering output, f3、f4Indicate the pixel value of boundary other side filtering output.
Further, the block size of pixel is 8 and the block distortion type of only boundary side is block noise unobvious, is made an uproar in block The unconspicuous boundary side of sound carries out linear filtering processing.
Further, the block size of pixel is 4 and when the block distortion type of boundaries on either side is that the block noise is apparent, choosing The noise reduction filtering algorithm taken is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△8)
f2=CLIP_0_255 (p2+△8)
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p0Indicate the pixel value that the boundary other side does not filter, f1、f2Indicate the pixel value of boundary side filtering output.
Further, the block size of pixel is 4 and the block distortion type of boundary side is that block noise is apparent, the boundary other side Block distortion type be block noise unobvious when, the noise reduction filtering algorithm of selection is as follows：
f1=(p0+p1+1)>>1
Wherein, p1Indicate boundary side pixel value to be filtered, p0Indicate the pixel value that the boundary other side does not filter, f1Table Show the pixel value of boundary side filtering output.
Further, it when the block size of pixel is block noise unobvious for the block distortion type of 4 and boundaries on either side, chooses Noise reduction filtering algorithm it is as follows：
f1=(p2+4×p1+3×p0+4)>>3
Wherein, p1Indicate boundary side pixel value to be filtered, p2Indicate the pixel value that boundary side does not filter, p0It indicates The pixel value that the boundary other side does not filter.
The denoising device of picture noise of the present invention, including：
Mosquito noise denoiser, for being filtered place to pixel according to the pixel value and filtration coefficient of pixel to be filtered Reason；
Noise reduction intensity controller, for carrying out intensity to filtered initial noise reduction pixel using noise reduction intensity control algorithm Compensation deals obtain final noise reduction pixel.
The present invention threshold value is determining, index obtains is carried out to macro block in decoding image and adaptive smooth to mosquito noise into Row is filtered, and improves the noise reduction of mosquito noise, the image after noise reduction shows clear.
It should be understood that above general description and following detailed description is merely exemplary, this can not be limited It is open.
Description of the drawings
Its example embodiment is described in detail by referring to accompanying drawing, above and other target, feature and the advantage of the disclosure will It becomes more fully apparent.
Fig. 1 is the flow diagram of the noise-reduction method of mosquito noise in picture noise of the present invention；
Fig. 2 is the binary index schematic diagram of pixel value in the macro block for decoding image inputted；
Fig. 3 is the schematic diagram of filtration coefficient in predetermined filtering algorithm；
Fig. 4 is the flow diagram of the noise-reduction method of block distortion in picture noise of the present invention；
Fig. 5 is the schematic diagram of the pixel for block distortion noise reduction marginal analysis；
Fig. 6 is the schematic diagram that the block size of pixel defines；
Boundaries on either side that Fig. 7 is pixel block size when being 8 is the schematic diagram of the apparent input pixel to be filtered of block distortion；
Fig. 8 is pixel block size when being 8, and boundaries on either side is that block distortion is apparent and block distortion is unconspicuous to be filtered defeated Enter the schematic diagram of pixel；
Boundaries on either side that Fig. 9 is pixel block size when being 8 is the schematic diagram of the unconspicuous input pixel to be filtered of block distortion；
The filtering schematic diagram that Figure 10 is pixel block size when being 8；
Boundaries on either side that Figure 11 is pixel block size when being 4 is the schematic diagram of the apparent input pixel to be filtered of block distortion；
Figure 12 is pixel block size, and only boundary side is the signal of the apparent input pixel to be filtered of block distortion when being 4 Figure；
Boundaries on either side that Figure 13 is pixel block size when being 4 is the signal of the unconspicuous input pixel to be filtered of block distortion Figure.
Specific implementation mode
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, thesing embodiments are provided so that the disclosure will more Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Attached drawing is only the disclosure Schematic illustrations, be not necessarily drawn to scale.Identical reference numeral indicates same or similar part in figure, thus Repetition thereof will be omitted.
In addition, described feature, structure or characteristic can be incorporated in one or more implementations in any suitable manner In mode.In the following description, many details are provided to fully understand embodiment of the present disclosure to provide.So And it will be appreciated by persons skilled in the art that one in the specific detail can be omitted with technical solution of the disclosure Or more, or other methods, constituent element, device, step may be used etc..In other cases, it is not shown in detail or describes Known features, method, apparatus, realization, material or operation are to avoid a presumptuous guest usurps the role of the host and all aspects of this disclosure is made to become mould Paste.
The spatially relative terms such as "upper", "lower", "left", "right" can be used herein for ease of explanation, be used for Relationship of the elements or features relative to another elements or features shown in definition graph.It should be understood that in addition to figure Shown in except orientation, spatial terminology is intended to include the different direction of device in use or operation.For example, if in figure Device be squeezed, the element for being stated as being located at other elements or feature "lower" will be located into other elements or feature "upper". Therefore, exemplary term "lower" can include both upper and lower orientation.Device can also be positioned in other ways, such as rotate 90 Degree is located at other orientation, can be interpreted accordingly used herein of the opposite explanation in space.
As shown in Figure 1, in picture noise of the present invention mosquito noise noise-reduction method, include the following steps：
Step S10：Determine the block threshold value and block gray scale dynamic range of macro block in the decoding image of input；
Step S20：According to the comparison result of the pixel value of pixel in macro block and the block threshold value of macro block, pixel in macro block is obtained The binary of value indexes；
Step S30：Pixel to be filtered in macro block is determined according to the binary index of pixel value in macro block；
Step S40：The pixel to be filtered is filtered using scheduled filtering algorithm；
Step S50：Intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, is obtained To final noise reduction pixel.
The present invention threshold value is determining, index obtains is carried out to macro block in decoding image and adaptive smooth to mosquito noise into Row is filtered, and improves the noise reduction of mosquito noise, the image after noise reduction shows clear.
The solution of the present invention is understood to make those skilled in the art become apparent from, below to step S10, step S20, step Detailed description are as follows for S30 details：
Step S10：Determine the block threshold value and block gray scale dynamic range of macro block in the decoding image of input.
For example, threshold value determination process is carried out in two steps：
1. the inside of the block k in decoding image, calculates minimum and maximum gray value.
2. indicating the dynamic range setting of block gray scale by thresh [k] block threshold values indicated and by range [k] such as Under：
Thresh [k]=(max [k]+min [k]+1)/2
Range [k]=max [k]-min [k],
Wherein max [k] is the max pixel value of whole pixels in block k, and min [k] is the minimum pixel of whole pixels in block k Value.
Sometimes for increasing by a step, the step of increase, only uses when there is bright block, enables block gray scale in adjacent four bright blocks Dynamic range maximum value be max_range, kmaxIt is defined as the index of a block with the maximum value, i.e. max_range =range [kmax].It needs that block threshold value reset such as lower threshold value at this time to calculate.It is as follows that threshold value resets the pseudo-code calculated：
For (k=1；k<5；k++)
{
if(range[k]<32&&max_range>=64)
Thresh [k]=thresh [kmax]；
if(max_range<16)
Thresh [k]=0；
}
The above pseudo-code is according to the maximum value of dynamic range between the dynamic range of current block gray scale and four luminance blocks come really Fixed final block threshold value.Also that is, if block gray scale dynamic range is less than 32 and the maximum value of block gray scale dynamic range is more than or equal to When 64, the block threshold value of macro block is equal to the block threshold value of block gray scale dynamic range maximum value；Such as the maximum value of fruit block gray scale dynamic range When less than 16, the block threshold value of macro block is equal to 0.The step of increase, makes the wider result of range that this algorithm includes also relatively more accurate Really.
Step S20：According to the comparison result of the pixel value of pixel in macro block and the block threshold value of macro block, pixel in macro block is obtained The binary of value indexes.
Once it is determined that the threshold value thr of given block, then remaining operation is based only upon the progress of 8x8 blocks.The rec (h, v) is allowed to be respectively The pixel value of coordinate (h, v), wherein h, v=0,1,2 ..., 7, and bin (h, v) indexes for corresponding binary.So bin (h, v) can be obtained by following formula：
Step S30：Pixel to be filtered in macro block is determined according to the binary index of pixel value in macro block.
Fig. 2 defines the binary index of 8x8 block levels, and calculates 10x10 binary index to handle a 8x8 block.
When binary index only in 3x3 windows is all identical, that is, entirely " 0 " index or entirely " 1 " index When, filter could be applied.Shadow region indicates the pixel that will be filtered in Fig. 2.It note that 10x10 groups (set) binary indexes It is obtained by the single threshold value corresponding to 8x8 blocks.
Step S40：The pixel to be filtered is filtered using scheduled filtering algorithm.Specifically, it filters The pixel value flt'(h, v of wave device output) it is obtained by following equation：
Wherein coef (i, j) indicates that filtration coefficient, rec (h+i, v+j) are the pixel value of coordinate (h+i, v+j).
For the filtration coefficient indicated by coef (i, j) in block and in non-piece referring to Fig. 3, center pixel is here Number, i.e. coef (0,0).
The maximum gray scale between reconstructed pixel and Filtered Picture element changes according to quantization parameter after the step s 40, That is QP is limited.Allow flt (h, v) and flt'(h, v) be respectively filtered pixel value and limitation before pixel value.It is adopted Pseudo-code is as follows：
Step S50：Intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, is obtained To final noise reduction pixel.
Noise reduction intensity control algorithm is as follows in the present embodiment：
oblend=((s+1) × omnr+((3-s)×imnr+2)>>2
S is MNR strength control parameters, imnrTo be input to the input of mosquito noise noise reduction block, omnrFor the output of the block, oblendFor last strength control output valve.
It should be noted that the noise-reduction method of mosquito noise of the present invention also can be without follow-up after filtering noise reduction process Intensity compensation, directly output filtering noise reduction process after initial noise reduced pixel value, that is, omit the present invention in step S50, system that the present invention is not limited thereto.
The present invention also provides a kind of denoising device of the noise-reduction method corresponding to above-mentioned mosquito noise, mosquito noise noise reductions Device, for being filtered to pixel according to the pixel value and filtration coefficient of pixel to be filtered；Noise reduction intensity controller, is used for Intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, obtains final noise reduction pixel.
In addition, the distortion of mosquito formula may cause block to be distorted in the block boundary comprising mosquito noise.Therefore, in order to avoid block loses True problem can select to carry out block distortion noise reduction before mosquito noise noise reduction.The noise-reduction method of block distortion is done below As described below：
As shown in figure 4, the noise-reduction method of block distortion of the present invention, includes the following steps：
Step S10：According to the absolute difference and pixel value range of border side pixel in the block of pixels of input, analysis obtains institute State the block distortion type of border side pixel in block of pixels.
Step S20：It is chosen and is adapted to according to the block size of the block distortion type of boundaries on either side pixel in block of pixels and pixel Noise reduction filtering algorithm pixel in block of pixels is filtered.
Step S30：Intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, is obtained To final noise reduction pixel.
The present invention classifies to the block distortion of input pixel boundary both sides, chooses the drop for being suitable for different blocky noise types Filtering algorithm of making an uproar is filtered the pixel of boundaries on either side, improves the noise reduction of block distortion, the image after noise reduction It shows clear.
The solution of the present invention is understood to make those skilled in the art become apparent from, below to step S10, step S20, step Detailed description are as follows for S30 details：
Step S10：According to the absolute difference and pixel value range of border side pixel in the block of pixels of input, analysis obtains institute State the block distortion type of border side pixel in block of pixels.
For example, analytical procedure checks one group of 4 × BlkBoundarySize pixel to pass through each side on each boundary Absolute difference and pixel value range are classified as belonging to one kind in four classes listed in table 1.
Table 1:The BNR of border side classifies
In table 1, NOT_BLOCKY refers to no block noise, REAL_EDGE refers to true content information, BLOCKY_NONSMOOTH refers to Block noise unobvious, that BLOCKY_SMOOTH refers to block noise is apparent.
The absolute difference of border side and pixel value range can be obtained by calculating, and can also be directly acquired from outside, the present invention It is not limited thereto.The absolute difference of border side and pixel coverage can for example be calculated by the following formula to obtain：
Absolute difference MAD [n] is calculated between boundary and along its length and at two positions close to the boundary Average, n=0-2, pixel as shown in Figure 5 are defined.
P indicates pixel value, blkSize Indicate block size；
To each group be parallel to along its whole length in two groups of pixels on the boundary, the range RANGE of pixel value is calculated [n], n=1-2 are also shown in FIG. 5.
In the formula of top, p indicates that pixel value, blkBoundarySize indicate block size.
Following pseudo-code indicates the analysis operation carried out to RANGE [n] and MAD [n] to derive the block visibility class of table 1 Type.
This analysis determines, for every side on the boundary, it is close whether the vertical MAD [1] between boundary is significantly greater tnan The vertical MAD ([0] or MAD [2]) on the boundary.If it is not, then it is not block noise that the side on the boundary, which is categorized into,.
In other cases, which is block noise or is that the boundary includes picture edge characteristic.If the model The maximum value enclosed bigger compared with the vertical MAD [1] between boundary, then border side is block-like in non-smooth region, and Two ranges differ by more than programmable threshold, indicate block noise unobvious.
If this test crash, and MAD [1] exceeds threshold value, then the boundary includes picture edge characteristic.Otherwise, The border side is block-like in smooth region, indicates that block noise is apparent.It is emphasized that each side of this analysis for boundary Independently carry out.
Step S20：It is chosen and is adapted to according to the block size of the block distortion type of boundaries on either side pixel in block of pixels and pixel Noise reduction filtering algorithm pixel in block of pixels is filtered.
Specifically, after analysis obtains boundaries on either side pixel bulk noise type, by the information from both sides combine with Filtering order is generated, these filtering orders are applied to each side on the boundary later, as shown in table 2.It note that the filtering order It is specific for every side on the boundary.
Table 2
FILTER_LT indicates that the filtering order on the left of boundary or top, FILTER_RB are indicated for boundary in table 2 The filtering order on right side or bottom.
It is also noted that be block-like and the other side is NOT_BLOCKY although it is possible to wherein side, but can not possibly wherein Side is BLOCKY_SMOOTH and the other side is BLOCKY_NONSMOOTH.REAL_EDGE is also impossible to classify with any other Mixing.
In addition to the classification of border side, filtering generally depends on the block size perpendicular to boundary.Most of compression methods are not permitted Perhaps in addition to square block-shaped, but VC-1 allows 8x4 and 4x8 to convert block size.Block size for filtering is defined as The length of block on the direction perpendicular to boundary in research, and on the other side defined in filtering.Fig. 6 shows border side The pixel schematic diagram that block size is 8 and block size is 4.
1) for the strong filtering of boundary B LOCKY_SMOOTH on both sides
Referring to table 2, when block size is 8 and the block distortion type of boundaries on either side is BLOCKY_SMOOTH, on boundary There is the boundary of smooth block on both sides, and block is visible, becomes smooth surface fitting type using ambassador's bulk Filter both sides are filtered by force.
The noise reduction filtering algorithm of selection is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△/8)
f2=CLIP_0_255 (p2+2△/8)
f3=CLIP_0_255 (p3+△/8)
Here x is limited in range [0,255] by CLIP_0_255 (x).
As shown in Figure 7, wherein p1、p2、p3Indicate boundary side pixel value to be filtered, p0Indicate that the boundary other side is not filtered The pixel value of wave, f1、f2、f3Indicate the pixel value of boundary side filtering output.
It is the unilateral explanation of both sides operation above.Particularly, it is noted that, for the filtering on the other side on boundary, Δ Symbol be opposite.Alternatively, considerably, if Δ keeps identical for both sides, the other side will subtract the item including Δ, Rather than add these.Whole division arithmetics can be used as displacement to carry out, and round up.
2) for the MEDIUM (medium) on the boundaries BLOCKY_SMOOTH/NOT_BLOCKY and WEAK (weak) filter
Referring to table 2, the block size of pixel is 8 and the block distortion type of boundary side is BLOCKY_SMOOTH, boundary When the block distortion type of the other side is NOT_BLOCKY, medium filtering is carried out in the apparent side of block distortion, in no block noise Side carries out weak filtering.
The noise reduction filtering algorithm of selection is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+△/2)
f2=CLIP_0_255 (p2+△/8)
f0=CLIP_0_255 (p0-△/8)
As shown in Figure 6, wherein p1、p2Indicate boundary side pixel value to be filtered, p0Indicate that the boundary other side is to be filtered Pixel value, f1、f2Indicate the pixel value of boundary side filtering output, f0Indicate the pixel value of boundary other side filtering output.
3) for LINEAR (linear) filter of BLOCKY_NONSMOOTH border sides
In the unconspicuous region of block noise, surface fitting technology may cause to be distorted.Linear smoothing filter can generate Preferable result.The filtering algorithm of used linear filter is as follows：
f1=(p0+2×p1+p2+2)>>2
f2=(p1+4×p2+3×p3+4)>>3
f3=(3 × p2+4×p3+p4+4)>>3
f4=(p3+2×p4+p5+2)>>2
As shown in Figure 9, wherein p1、p2Indicate boundary side pixel value to be filtered, p3、p4Indicate that the boundary other side is to be filtered The pixel value of wave, p0Indicate the pixel value that boundary side does not filter, p5Indicate the pixel value that the boundary other side does not filter, f1、f2Table Show the pixel value of boundary side filtering output, f3、f4Indicate the pixel value of boundary other side filtering output.
The above filtering algorithm is suitable for both sides when being BLOCKY_NONSMOOTH.When only side is BLOCKY_ When NONSMOOTH, the other side is without filtering.Figure 10 shows filtering schematic diagram when the above pixel block size is 8.
Filtering side when block size is 8 and selected by boundaries on either side different masses noise type is described in above-described embodiment Formula is different from the filtering that block size is 8, boundary two when block size exemplified below is 4 it should be noted that block size is 4 filtering Filtering mode selected by the difference noise type of side.
1) in the strong filtering that boundaries on either side is BLOCKY_SMOOTH
When the block size of pixel is 4 and the block distortion type of boundaries on either side is BLOCKY_SMOOTH, the noise reduction of selection Filtering algorithm is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△/8)
f2=CLIP_0_255 (p2+△/8)
As shown in figure 11, wherein p1、p2Indicate boundary side pixel value to be filtered, p0Indicate that the boundary other side does not filter Pixel value, f1、f2Indicate the pixel value of boundary side filtering output.
2) medium filtering for being BLOCKY_SMOOTH in boundary unilateral side
When the block size of pixel is 4 and the block distortion type of boundary unilateral side is BLOCKY_SMOOTH, weak filtering is in block Size does not filter in the case of being 4, is only filtered to a pixel, the noise reduction filtering algorithm of selection is as follows：
f1=(p0+p1+1)>>1
As shown in figure 12, wherein p1Indicate boundary side pixel value to be filtered, p0Indicate what the boundary other side did not filtered Pixel value, f1Indicate the pixel value of boundary side filtering output.
3) be in boundaries on either side BLOCKY_NONSMOOTH linear filtering
When the block size of pixel is 4 and the block distortion type of boundaries on either side is BLOCKY_NONSMOOTH, selection Noise reduction filtering algorithm is as follows：
f1=(p2+4×p1+3×p0+4)>>3
As shown in figure 13, wherein p1Indicate boundary side pixel value to be filtered, p2Indicate the picture that boundary side does not filter Element value, p0Indicate the pixel value that the boundary other side does not filter.
Step S30：Intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, is obtained To final noise reduction pixel.
Noise reduction intensity control algorithm is as follows in the present embodiment：
oblend=((s+1) × obnr+((3-s)×ibnr+2)>>2
Wherein, s is block noise noise reduction strength control parameter, and ibnr is input pixel value, and obnr is by noise reduction process Initial noise reduced pixel value, oblend are final noise reduced pixel value.Noise reduction strength control will be non-filtered according to above formula formula Initial input pixel value with Jing Guo noise reduction process initial noise reduced pixel value mixing, to carry out intensity compensation processing so that most Final decline make an uproar pixel noise reduction it is more preferable, the image after noise reduction show it is clear, avoid image display distortion and it is fuzzy the problems such as.
It should be noted that the noise-reduction method of block distortion of the present invention also can be without follow-up after filtering noise reduction process Intensity compensation, directly output filtering noise reduction process after initial noise reduced pixel value, that is, omit the present invention in step S30, system that the present invention is not limited thereto.
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure The technical solution of embodiment can be expressed in the form of software products, the software product can be stored in one it is non-volatile Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating Equipment (can be personal computer, server, mobile terminal or network equipment etc.) is executed according to disclosure embodiment Method.
It should be noted that each embodiment in this specification is described in a progressive manner, each embodiment weight Point explanation is all difference from other examples, and the same or similar parts between the embodiments can be referred to each other.
For convenience of description, it describes to be divided into various modules when system above or device with function or unit describes respectively. Certainly, the function of each unit is realized can in the same or multiple software and or hardware when implementing the application.
As seen through the above description of the embodiments, those skilled in the art can be understood that the application can It is realized by the mode of software plus required general hardware platform.Based on this understanding, the technical solution essence of the application On in other words the part that contributes to existing technology can be expressed in the form of software products, the computer software product It can be stored in a storage medium, such as ROM/RAM, magnetic disc, CD, including some instructions are used so that a computer equipment (can be personal computer, server either network equipment etc.) executes the certain of each embodiment of the application or embodiment Method described in part.
Finally, it is to be noted that, herein, such as first, second, third and fourth or the like relational terms It is only used to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying these There are any actual relationship or orders between entity or operation.Moreover, the terms "include", "comprise" or its is any Other variants are intended to non-exclusive inclusion, so that including the process, method, article or equipment of a series of elements Include not only those elements, but also include other elements that are not explicitly listed, or further includes for this process, side Method, article or the intrinsic element of equipment.In the absence of more restrictions, limited by sentence "including a ..." Element, it is not excluded that there is also other identical elements in the process, method, article or apparatus that includes the element.
It is particularly shown and described the illustrative embodiments of the disclosure above.It should be appreciated that the disclosure is unlimited In detailed construction described herein, set-up mode or implementation method；On the contrary, disclosure intention covers included in appended claims Spirit and scope in various modifications and equivalence setting.

Claims (8)

1. a kind of noise-reduction method of block distortion, which is characterized in that include the following steps：
1) according to the absolute difference and pixel value range of border side pixel in the block of pixels of input, analysis obtains in the block of pixels The block distortion type of border side pixel；
2) noise reduction filtering of adaptation is chosen according to the block size of the block distortion type of boundaries on either side pixel in block of pixels and pixel Algorithm is filtered pixel in block of pixels.
2. noise-reduction method as described in claim 1, which is characterized in that the noise-reduction method further includes：
3) intensity compensation processing is carried out to filtered initial noise reduction pixel using noise reduction intensity control algorithm, obtains final noise reduction Pixel.
3. noise-reduction method as claimed in claim 2, which is characterized in that the noise-reduction method further includes：
4) selectivity output input pixel or the final noise reduction pixel.
4. noise-reduction method as described in claim 1, which is characterized in that further include before step 1)：
Calculate the absolute difference and pixel value range of border side pixel in the block of pixels of input.
5. noise-reduction method as described in claim 1, which is characterized in that the block distortion type of the pixel includes that no block is made an uproar Sound, real border, block noise be apparent and block noise unobvious.
6. noise-reduction method as claimed in claim 5, which is characterized in that when the block distortion type of boundaries on either side is described piece When noise is apparent：
If the block size of pixel is 8, the noise reduction filtering algorithm chosen is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△/8)
f2=CLIP_0_255 (p2+2△/8)
f3=CLIP_0_255 (p3+△/8)
Wherein, p1、p2、p3Indicate boundary side pixel value to be filtered, p0Indicate the pixel value that the boundary other side does not filter, f1、 f2、f3Indicate that x is limited between [0,255] by the pixel value of boundary side filtering output, CLIP_0_255 (x) expressions；
If the block size of pixel is 4, the noise reduction filtering algorithm chosen is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+3△/8)
f2=CLIP_0_255 (p2+△/8)
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p0Indicate the pixel value that the boundary other side does not filter, f1、f2Table Show that x is limited between [0,255] by the pixel value of boundary side filtering output, CLIP_0_255 (x) expressions.
7. noise-reduction method as claimed in claim 5, which is characterized in that when the block distortion type of boundary side is that block noise is bright It is aobvious, the block distortion type of the boundary other side for no block noise when：
If the block size of pixel is 8, the noise reduction filtering algorithm chosen is as follows：
△=p0-p1
f1=CLIP_0_255 (p1+△/2)
f2=CLIP_0_255 (p2+△/8)
f0=CLIP_0_255 (p0-△/8)
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p0Indicate boundary other side pixel value to be filtered, f1、f2Table Show the pixel value of boundary side filtering output, f0Indicate that the pixel value of boundary other side filtering output, CLIP_0_255 (x) indicate X is limited between [0,255]；
If the block size of pixel is 4, the noise reduction filtering algorithm chosen is as follows：
f1=(p0+p1+1)>>1
Wherein, p1Indicate boundary side pixel value to be filtered, p0Indicate the pixel value that the boundary other side does not filter, f1Indicate side The pixel value of boundary side filtering output.
8. noise-reduction method as claimed in claim 5, which is characterized in that when the block distortion type of boundaries on either side is block noise When unobvious：
If the block size of pixel is 8, the noise reduction filtering algorithm chosen is as follows：
f1=(p0+2×p1+p2+2)>>2
f2=(p1+4×p2+3×p3+4)>>3
f3=(3 × p2+4×p3+p4+4)>>3
f4=(p3+2×p4+p5+2)>>2
Wherein, p1、p2Indicate boundary side pixel value to be filtered, p3、p4Indicate boundary other side pixel value to be filtered, p0Table Show the pixel value that boundary side does not filter, p5Indicate the pixel value that the boundary other side does not filter, f1、f2Indicate the filtering of boundary side The pixel value of output, f3、f4Indicate the pixel value of boundary other side filtering output；
If the block size of pixel is 4, the noise reduction filtering algorithm chosen is as follows：
f1=(p2+4×p1+3×p0+4)>>3
Wherein, p1Indicate boundary side pixel value to be filtered, p2Indicate the pixel value that boundary side does not filter, p0Indicate boundary The pixel value that the other side does not filter, f1Indicate the pixel value of boundary side filtering output.
CN201810303006.4A 2018-04-06 2018-04-06 The noise-reduction method and device of block distortion Pending CN108337509A (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101389016A (en) * 2007-09-13 2009-03-18 华为技术有限公司 Method and device for obtaining boundary strength and removing block effect
CN101540900A (en) * 2008-03-20 2009-09-23 矽统科技股份有限公司 Method for reducing block effect in video streaming
CN103891284A (en) * 2011-10-27 2014-06-25 索尼公司 Image processing device and method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101389016A (en) * 2007-09-13 2009-03-18 华为技术有限公司 Method and device for obtaining boundary strength and removing block effect
CN101540900A (en) * 2008-03-20 2009-09-23 矽统科技股份有限公司 Method for reducing block effect in video streaming
CN103891284A (en) * 2011-10-27 2014-06-25 索尼公司 Image processing device and method

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Application publication date: 20180727