Method of processing an image based on the determination of blockiness level
View Patent ↗A method for processing an image divided into blocks of pixels is described. The method includes detecting a largest sub-block whose pixels have an equal luminance value and identifying if the detected largest sub-block is or is not a natural texture. Thereafter, a weighted luminance difference is calculated between the detected largest sub-block and neighboring pixels and a block blockiness level is determined on the basis of the number of pixels within the detected largest sub-block, of the identification step and of the weighted luminance difference. The image is then processed on the basis of the block blockiness level.
1. A method for processing an image divided into blocks of pixels, the method comprising:
detecting, for each block, a largest sub-block whose pixels have an equal luminance value; and,
identifying, for each block, if the detected largest sub-block is or is not a natural texture;
calculating, for each block, a weighted luminance difference between the detected largest sub-block and neighboring pixels;
determining, for each block, a block blockiness level on the basis of the number of pixels within the detected largest sub-block determined by said identifying and said weighted luminance difference; and
processing said image on the basis of said block blockiness levels.
2. The method according to claim 1 , said method further comprising determining an image blockiness level for said image by averaging the block blockiness levels and wherein said image is processed on the basis of said image blockiness level.
3. The method according to claim 1 , wherein said processing comprises one of:
encoding said image;
filtering said image; and
distributing said image.
4. The method according to claim 1 , wherein, when a deblocking filter is applied on said image, identifying the detected largest sub-block as natural texture when the detected largest sub-block reaches at least two opposite block borders.
5. The method according to claim 1 , wherein, when no deblocking filter is applied on said image or when no information is provided on applying or not applying a deblocking filter, identifying the detected largest sub-block as natural texture when the detected largest sub-block exceeds at least two opposite block borders.
6. The method according to claim 1 , wherein the determining a block blockiness level comprises:
determining a preliminary block blockiness level on the basis of the number of pixels within the detected largest sub-block and on the basis of the results of the identification step; and
adjusting said preliminary block blockiness level as a function of the weighted luminance difference, said function depending on a blockiness sensitivity.
7. The method according to claim 6 , wherein the preliminary block blockiness level BBL for a block is calculated as follows:
BBL
=
{
0
when
the
detected
largest
subblock
is
natural
texture
1
when
T
2
≤
N
N
/
T
2
when
T
1
≤
N
<
T
2
0
when
N
<
T
1
where T1 and T2 are threshold values and N is the number of pixels within the detected largest sub-block.
8. The method according to claim 6 , wherein the preliminary block blockiness level BBL for a block is calculated as follows:
BBL
=
{
0
when
the
detected
largest
subblock
is
a
natural
texture
1
when
T
2
≤
N
0.5
when
T
1
≤
N
<
T
2
0
when
N
<
T
1
where T1 and T2 are threshold values and N is the number of pixels within the detected largest sub-block.
9. An apparatus configured to process an image divided into blocks of pixels, the apparatus comprising:
a memory; and
a processor configured to:
detect, for each block, a largest sub-block whose pixels have an equal luminance value; and,
identify, for each block, whether the detected largest sub-block is a natural texture;
calculate, for each block, a weighted luminance difference between the detected largest sub-block and neighboring pixels;
determine, for each block, a block blockiness level based on a number of pixels within the detected largest sub-block and said weighted luminance difference; and
process said image based on said block blockiness levels.
10. The apparatus according to claim 9 , wherein the processor is further configured to determine an image blockiness level for said image by averaging the block blockiness levels and wherein said image is processed based on said image blockiness level.
11. The apparatus according to claim 9 , wherein to process said image the processor is configured to encode said image, filter said image, or distribute said image.
12. The apparatus according to claim 9 , wherein, when a deblocking filter is applied on said image, the processor is configured to identify the detected largest sub-block as natural texture when the detected largest sub-block reaches at least two opposite block borders.
13. The apparatus according to claim 9 , wherein, when no deblocking filter is applied on said image or when no information is provided on applying or not applying a deblocking filter, the processor is configured to identify the detected largest sub-block as natural texture when the detected largest sub-block exceeds at least two opposite block borders.
14. The apparatus according to claim 9 , wherein to determine a block blockiness level, the processor is configured to:
determine a preliminary block blockiness level based on the number of pixels within the detected largest sub-block and whether the detected largest sub-block is the natural texture; and
adjust said preliminary block blockiness level as a function of the weighted luminance difference, said function depending on a blockiness sensitivity.
15. The apparatus according to claim 14 , wherein the preliminary block blockiness level (BBL) for a block is calculated as follows:
BBL
=
{
0
when the detected largest sub-block is a
natural texture
1
when
T
2
≤
N
N
/
T
2
when
T
1
≤
N
<
T
2
0
when
N
<
T
1
where T1 and T2 are threshold values and N is the number of pixels within the detected largest sub-block.
16. The apparatus according to claim 14 , wherein the preliminary block blockiness level (BBL) for a block is calculated as follows:
BL
=
{
0
when the detected largest sub-block is a
natural texture
1
when
T
2
≤
N
0.5
when
T
1
≤
N
<
T
2
0
when
N
<
T
1
where T1 and T2 are threshold values and N is the number of pixels within the detected largest sub-block.