Signal adaptive filtering method and signal adaptive filter for reducing blocking effect and ringing noise

• US 6,259,823 B1
• Filed: 10/22/1997
• Issued: 07/10/2001
• Est. Priority Date: 02/15/1997
• Status: Expired due to Term

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Park, Hyun-wook, Lee, Yung-lyul
• Primary Examiner(s): Lee, Thomas D.
• Assistant Examiner(s): BRINICH, STEPHEN M
• Application Number:
  US08/956,036
• Time in Patent Office: 1,357 Days
• Field of Search: 382/268, 382/199, 382/266-267, 382/269, 382/260-261
• US Class Current: 382/268
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 9/00 Image coding bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00
• CPC Class Codes: H04N 19/117 Filters, e.g. for pre-processing or post-processing sub-band filter banks H04N19/635
• CPC Class Codes: H04N 19/14 Coding unit complexity, e.g. amount of activity or edge presence estimation H04N19/146 takes precedence
• CPC Class Codes: H04N 19/527 Global motion vector estimation

Abstract

A signal adaptive filtering method is disclosed for reducing a blocking effect and ringing noise of an image data.

A gradient of the image data is calculated for each pixel of the image data. Then, the gradient data of each pixel is compared with a global threshold value (T_g) which is determined based on a predetermined quantization step size (Q), and global edge map information of the pixel is generated. Meanwhile, the gradient data of each pixel is compared with a local threshold value (T_n) determined for each block having a predetermined size, and local edge map information of the pixel is generated. An OR operation is performed with respect to the global edge map information and the local edge map information to generate binary edge map information. Then, a predetermined sized filter window is applied to determine whether edges are present in the binary edge map information within the filter window. Afterwards, the image data pixel values of the corresponding filter window are filtered, pixel by pixel, by using predetermined first weighted values to generate a first new pixel value if it is determined that edges are not present. The image data pixel values within the corresponding filter window are filtered, pixel by pixel, by using predetermined second weighted values to generate a second new pixel value if it is determined that edges are present within the window. No filtering is performed if the pixel located at the center of the filter window represents an edge.

Claims

1. A signal adaptive filtering method for reducing a blocking effect and ringing noise in image data, the image data including a plurality of pixels divided into predetermined sized blocks, the method comprising:

(a) calculating a gradient of the image data at each pixel of the image data;

(b) comparing the gradient of each pixel with a global threshold value (T_g) determined based on a predetermined quantization step (Q) to generate global edge map information for the pixel;

(c) comparing the gradient of each pixel with a local threshold value (T_n) determined for each block to generate local edge map information for the pixel;

(d) performing an OR operation on the global edge map information generated in (b) and the local edge map information generated in (c), to generate binary edge map information;

(e) applying a filter window of a predetermined size to determine whether edges are present in the image data within the filter window based on the binary edge map information;

(f) filtering the image data within the filter window, pixel by pixel, by using predetermined first weighted values to generate a first new pixel value if it is determined in (e) that edges are not present; and

(g) filtering the pixel values of the corresponding filter window, pixel by pixel, by using predetermined second weighted values to generate a second new pixel value if it is determined in (e) that edges are present, wherein the filtering in (f) and (g) are not performed if the pixel located at the center of the filter window represents an edge.

2. A signal adaptive filtering method as claimed in claim 1, wherein the global threshold value (T_g) in (b) is determined by:

$T_g=\{\begin{array}{cc}4<br><br>Q+60,& 6\le <br><br>Q\le <br><br>18\\ 84,& Q\le <br><br>5\\ 132,& Q\ge <br><br>19\end{array}$

where Q is a quantization step of a quantizer.

3. A signal adaptive filtering method as claimed in claim 2, wherein T_n is an n-th local threshold value calculated by:

$T_n=\left|1-\frac{{\mathrm{\sigma <br><br>}}_n}{m_n}\right|*T_g$$\mathrm{where},<br><br>{\mathrm{\sigma <br><br>}}_n=\sqrt{\frac{1}{N}<br><br>\underset{\left(i,j\right)<br><br>\mathrm{\epsilon <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>R_n}{\sum <br><br>}<br><br>{\left\{g<br><br>\left(i,j\right)-m_n\right\}}^2}$$m_n=\frac{1}{N}<br><br>\underset{\left(i,j\right)·<br><br>\mathrm{\epsilon <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>R_n}{\sum <br><br>}<br><br>g<br><br>\left(i,j\right)$

and g(i,j) represents the calculated gradient for pixel (i,j) of the image data image, R_n represents an n-th 8×

8 block, m_n and σ

_n denote the average and standard deviation, respectively, of the calculated gradient of the pixels of the n-th 8×

8 block.

4. A signal adaptive filtering method as claimed in claim 3, wherein in (c), the gradient of each of 6×

6 pixels which result from excluding boundary pixels from an 8×

8 size block, are compared with the local threshold value to generate the local edge map information.

5. A signal adaptive filtering method as claimed in claim 1, wherein the filter window is 3×

3 pixels in size.

6. A signal adaptive filtering method as claimed in claim 2, wherein the filter window is 3×

3 pixels in size.

7. A signal adaptive filtering method as claimed in claim 5, wherein in (f) the predetermined first weighted values are equal to 1.

8. A signal adaptive filtering method as claimed in claim 6, wherein in (f) the predetermined first weighted values are equal to 1.

9. A signal adaptive filtering method as claimed in claim 5, wherein in (g) the weighted value applied to the pixel located at the center of the 3×

3 filter window is equal to 2.

10. A signal adaptive filter comprising:

an image storing unit for temporarily storing decompressed image data;

a gradient operation unit for receiving the image data in block units of a predetermined size from said image storing unit, calculating a gradient of the image data in the horizontal and vertical directions by using gradient operators to find edge pixels, and outputting gradient data;

a global edge map generator for comparing the gradient data output by said gradient operation unit with a global threshold value (T_g) determined based on a quantization step (Q) to generate binary global edge map information;

a local edge map generator for comparing, pixel by pixel, the gradient data output by said gradient operation unit with a local threshold value which is individually determined for each block to generate binary local edge map information;

an OR-gate for OR-operating, pixel by pixel, the global edge map information generated by the global edge map generator and the local edge map information generated by the local edge map generator to generate binary edge map information;

a filter selector for storing the binary edge map information output by said OR-gate and classifying the image data into an edge area including information of at least one edge and a homogeneous area without information of any edges, according to the binary edge map information;

an average filter for performing an average filtering on a central pixel within a filtering window of a filtering area, when the filtering area is classified by the filter selector as a homogeneous area, to generate a first new pixel value; and

a weighted filter for performing a weighted filtering on the central pixel within the filtering window of the filtering area, when the filtering area is classified by the filter selector as an edge area, to generate a second new pixel value.

11. A signal adaptive filter as claimed in claim 10, wherein the global threshold value (T_g) is determined in said global edge map generator according to:

$T_g=\{\begin{array}{cc}4<br><br>Q+60,& 6\le <br><br>Q\le <br><br>18\\ 84,& Q\le <br><br>5\\ 132,& Q\ge <br><br>19\end{array}$

where Q is a quantization step size of a quantizer.

12. A signal adaptive filtering method for reducing a blocking effect and ringing noise in image data, the image data including a plurality of pixels, the method comprising:

(a) determining a gradient of each of the pixels in the image data;

(b) detecting an edge in an area of the image data based on the gradient determined in (a); and

(c) performing only a first type of filtering on pixels within the image data area if an edge is detected in (b) and performing only a second type of filtering on pixels within the image data area if no edge is detected in (b);

wherein the detecting in (b) is performed by generating global and local edge map information based on the gradients of the pixels, and detecting the edge based on the global and local edge map information.

13. A signal adaptive filtering method as claimed in claim 12, wherein the local edge map information is generated based on gradient data of pixels forming a macroblock.

14. A signal adaptive filtering method as claimed in claim 12, wherein the first type of filtering is an average and the second type of filtering is a weighted filtering.

15. A signal adaptive filtering method for reducing a blocking effect and ringing noise in image data, the image data including a plurality of pixels, the method comprising:

(a) determining a gradient of the pixels in the image data;

(b) detecting an edge in an area of the image data based on the gradient determined in (a); and

(c) performing only a first type of filtering on pixels within the image data area if an edge is detected in (b) and performing only a second type of filtering on pixels within the image data area if no edge is detected in (b);

wherein the first and second types of filtering are performed on pixels within the image data area corresponding to a filtering window having a predetermined size, and wherein neither the first and second types of filtering is performed if the edge is detected for a pixel located in the center of the filtering window.