Abstract:
The present invention provides a noise reduction method for use in reducing noise of a digital image, the method comprising steps of: providing a plurality of luminance threshold values; determining a plurality of luminance feature values according to the luminance value of a target pixel and the luminance values of neighboring pixels of the target pixel; determining whether the target pixel is a noise point based on the comparison between each of the luminance feature values and each of the luminance threshold values corresponding thereto, respectively; and adjusting the luminance value, a first chrominance value and a second chrominance value of the target pixel if the target pixel is determined as a noise point. Using the noise reduction method of the present invention, not only noise of a digital image can be identified, but also the degradation caused by the noise can be reduced and thus the overall picture quality can be improved.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    1. Field of the Invention 
         [0002]    The present invention generally relates to a noise reduction method and apparatus and, more particularly, to a noise reduction method and apparatus using a luminance value of a target pixel and luminance values of neighboring pixels of the target pixel so as to identify and eliminate a noise point of a digital image. 
         [0003]    2. Description of the Prior Art 
         [0004]    In digital image processing, the most generally used method to reduce noise is to directly process the pixels related to the image. For example, averaging filters and sequence statistical filters are used according to respective requirements. 
         [0005]    Conventionally, impulse noise is eliminated using a median filter, which is a non-linear spatial filter operating corresponding to the pixel values in a neighboring region of a target pixel so as to sort the pixel values and then make the median pixel replace the target pixel. However, the median filter performs pixel adjustment for the entire image including some non-noise portions. Therefore, the noise reduction process using the median filter may lead to undesirable distortion of the image because it cannot identify where noise occurs. Moreover, since the pixel is adjusted according to the pixel values of the neighboring pixels, the adjusted image shows unnaturalness in luminance and chrominance. 
         [0006]    Accordingly, the present invention provides a noise reduction method not only to identify noise of a digital image, but also to reduce noise by adjusting the luminance value and the chrominance value to avoid image distortion. 
         [0007]    Compared to the prior art, the noise reduction method of the present invention exhibits excellent performance in noise reduction while remaining the original colors in the region where there is no noise determined. 
       SUMMARY OF THE INVENTION 
       [0008]    It is a primary object of the present invention to provide a noise reduction method so as to identify noise in a digital image and adjust the luminance value and the chrominance values of a pixel that is determined a noise point so that the image quality is improved and the image distortion is avoided. 
         [0009]    In order to achieve the foregoing object, the present invention provides a noise reduction method, comprising steps of: providing a plurality of luminance threshold values; determining a plurality of luminance feature values according to a luminance value of a target pixel and luminance values of neighboring pixels of the target pixel by a calculating unit of the display; determining whether the target pixel is a noise point, by a comparing unit of the display, based on the comparison between each of the luminance feature values and each of the luminance threshold values corresponding thereto, respectively; and adjusting the luminance value of the target pixel, by an adjusting unit of the display, when the target pixel is determined as the noise point. 
         [0010]    The luminance feature values are determined by: (1) the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming a cross shape; (2) the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming an X shape; (3) the luminance values of the neighboring pixels; or (4) the luminance value of the target pixel and a mean luminance value of the neighboring pixels. 
         [0011]    Preferably, the luminance feature value comprises a first luminance feature value, a second luminance feature value, a third luminance feature value and a fourth luminance feature value. The first luminance feature value is determined by the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming a cross shape. The second luminance feature value is determined by the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming an X shape. The third luminance feature value is determined by the luminance values of the neighboring pixels. The fourth luminance feature value is determined by the luminance value of the target pixel and a mean luminance value of the neighboring pixels. 
         [0012]    Preferably, the luminance threshold value comprises: a first luminance threshold value, a second luminance threshold value, a third luminance threshold value and a fourth luminance threshold value. The first luminance threshold value, the second luminance threshold value and the third luminance threshold value are pre-determined. The fourth luminance threshold value is determined by the luminance values of the neighboring pixels of the target pixel and the mean luminance value of the neighboring pixels of the target pixel. 
         [0013]    Preferably, the first luminance feature value is larger than the first luminance threshold value, the second luminance feature value is larger than the second luminance threshold value, the third luminance feature value is smaller than the third luminance threshold value and the fourth luminance feature value is larger than the fourth luminance threshold value, so that the target pixel is determined a noise point. 
         [0014]    The step of adjusting the luminance value of the target pixel comprises steps of: selecting a luminance median from a series including the luminance value of the target pixel and the luminance values of the neighboring pixels; and performing a luminance weighting calculation so as to adjust the luminance value of the target pixel according to the luminance median. 
         [0015]    The step of adjusting the chrominance value of the target pixel comprises steps of: selecting a chrominance median from a series including the chrominance value of the target pixel and chrominance values of the neighboring pixels; and performing a chrominance weighting calculation so as to adjust the chrominance value of the target pixel according to the chrominance median. 
         [0016]    In order to achieve the foregoing object, the present invention provides a noise reduction apparatus, comprising: a calculating unit, for determining a plurality of luminance feature values according to a luminance value of a target pixel of the digital image and luminance values of neighboring pixels of the target pixel; a comparing unit, for determining whether the target pixel is a noise point based on the comparison between each of the luminance feature values and each of luminance threshold values corresponding thereto, respectively; and an adjusting unit, adjusting the luminance value of the target pixel when the target pixel is determined as the noise point. 
         [0017]    Accordingly, the present invention provides a noise reduction method using the luminance profile of the target pixel and its neighboring pixels to determine a plurality of luminance feature values to be compared with a plurality of luminance threshold values so as to determine whether the target pixel is infected with noise, which is to be eliminated by adjusting the luminance value and the chrominance value of the target pixel. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS  
         [0018]    The objects, spirits and advantages of the preferred embodiment of the present invention will be readily understood by the accompanying drawings and detailed descriptions, wherein: 
           [0019]      FIG. 1  is a flowchart showing steps of the noise reduction method according to the preferred embodiment of the present invention; 
           [0020]      FIG. 2  is a schematic diagram showing a target pixel and its neighboring pixels according to the preferred embodiment of the present invention; 
           [0021]      FIG. 3  is a detailed flowchart showing steps of the noise reduction method according to the preferred embodiment of the present invention; and 
           [0022]      FIG. 4  is a functional diagram of the noise reduction apparatus according to one embodiment of the present invention 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0023]    The present invention providing a noise reduction method and a noise reduction apparatus can be exemplified by the preferred embodiment as described hereinafter. 
         [0024]    The noise reduction method provided by the present invention can be applied in an image display such as TVs or monitors. Please refer to  FIG. 1 , which is a flowchart showing steps of the noise reduction method according to the preferred embodiment of the present invention. First, as described in Step S 101 , four luminance threshold values are provided. The first luminance threshold value, the second luminance threshold value and the third luminance threshold value are pre-determined. The fourth luminance threshold value is determined by the luminance values of the neighboring pixels of a target pixel and the mean luminance value of the neighboring pixels of the target pixel. 
         [0025]    Then, in Step S 102 , four luminance feature values are determined according to a luminance value of the target pixel and the luminance values of neighboring pixels of the target pixel. The first luminance feature value is determined by the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming a cross shape. The second luminance feature value is determined by the luminance value of the target pixel and the luminance values of four neighboring pixels, the target pixel and the four neighboring pixels forming an X shape. The third luminance feature value is determined by the luminance values of the neighboring pixels. The fourth luminance feature value is determined by the luminance value of the target pixel and a mean luminance value of the neighboring pixels. In one embodiment, the Step S 102  can be performed by a calculating unit of a display when the noise reduction method is applied in the display. 
         [0026]    In Step S 103 , each luminance feature value and each luminance threshold value are compared so as to determine whether the target pixel is a noise point. The first luminance feature value is larger than the first luminance threshold value, the second luminance feature value is larger than the second luminance threshold value, the third luminance feature value is smaller than the third luminance threshold value and the fourth luminance feature value is larger than the fourth luminance threshold value, so that the target pixel is determined a noise point. In one embodiment, the Step S 103  can be performed by a comparing unit of the display. 
         [0027]    Finally, in Step  104 , the luminance value and the chrominance value of the target pixel is adjusted if the target pixel is determined a noise point. The step of adjusting the luminance value of the target pixel comprises steps of: selecting a luminance median from a series including the luminance value of the target pixel and the luminance values of the neighboring pixels; and performing a luminance weighting calculation so as to adjust the luminance value of the target pixel according to the luminance median. The step of adjusting the chrominance value of the target pixel comprises steps of: selecting a chrominance median from a series including the chrominance value of the target pixel and chrominance values of the neighboring pixels; and performing a chrominance weighting calculation so as to adjust the chrominance value of the target pixel according to the chrominance median. In one embodiment, the Step S 104  can be performed by an adjusting unit of the display. 
         [0028]    Please refer to  FIG. 2 , which is a schematic diagram showing a target pixel and its neighboring pixels according to the preferred embodiment of the present invention. A 3×3 mask  20  comprises nine pixels, wherein the central pixel Pt is a target pixel and the neighboring pixels that forms a X shape with the target pixel are Pd 1 , Pd 2 , Pd 3 , Pd 4  and the neighboring pixels that forms a cross shape with the target pixel are Pr 1 , Pr 2 , Pr 3 , Pr 4 . When the target pixel Pt moves from one point in a digital image  22  to another, the mask  20  also moves. 
         [0029]    Please refer to  FIG. 3 , which is a detailed flowchart showing steps of the noise reduction method according to the preferred embodiment of the present invention. First, in Step S 300 , the luminance value of the target pixel and the luminance values of the neighboring pixels are determined so as to obtain a 3×3 matrix of luminance values, wherein Yt is the luminance value of the target pixel Pt; Yr1, Yr2, Yr3, Yr4 are luminance values corresponding to Pr 1 , Pr 2 , Pr 3 , Pr 4 , respectively; and Yd1, Yd2, Yd3, Yd4 are luminance values corresponding to Pd 1 , Pd 2 , Pd 3 , Pd 4 , respectively. 
         [0030]    Then, in Step  310 , the first luminance feature value CV 1 , the second luminance feature value CV 2 , the third luminance feature value CV 3 , and the fourth luminance feature value CV 4  are calculated. CV 1 , CV 2 , CV 3 , and CV 4  are expressed as: 
         [0000]        CV 1=abs[ Yr 1+ Yr 2+ Yr 3+ Yr 4 −K 1× Yt]   
         [0000]        CV 2=abs[ Yd 1+ Yd 2+ Yd 3+ Yd 4 −K 2× Yt]   
         [0000]        CV 3=abs[( Yd 1+ Yd 2+ Yd 3+ Yd 4)−( Yr 1+ Yr 2+ Yr 3+ Yr 4)] 
         [0000]        CV 4=abs[ Yt−Y _mean]× K 4 
         [0000]    where K1, K2, K3, K4 are constants, Y_mean is a mean value of Yr1, Yr2, Yr3, Yr4, Yd1, Yd2, Yd3, Yd4 and abs is an absolute value operator. 
         [0031]    Later in Step  320 , the first luminance threshold value Th 1 , the second luminance threshold value Th 2 , the third luminance threshold value Th 3 , and the fourth luminance threshold value Th 4  are calculated. Th 1 , Th 2 , Th 3 , and Th 4  are luminance threshold values corresponding to CV 1 , CV 2 , CV 3 , and CV 4 , respectively. The first luminance threshold value Th 1 , the second luminance threshold value Th 2  and the third luminance threshold value Th 3  are pre-determined. The fourth luminance threshold value Th 4  is expressed as: 
         [0000]        Th 4=abs[ Yr 1 −Y _mean] 
         [0000]      +abs[ Yr 2 −Y _mean] 
         [0000]      +abs[ Yr 3 −Y _mean] 
         [0000]      +abs[ Yr 4 −Y _mean] 
         [0000]      +abs[ Yd 1 −Y _mean] 
         [0000]      +abs[ Yd 2 −Y _mean] 
         [0000]      +abs[ Yd 3 −Y _mean] 
         [0000]      +abs[ Yr 4 −Y _mean] 
         [0032]    The Step S 310  and the Step S 320  are in no particular order. In other words, the luminance threshold values can be calculated prior to the calculation of the luminance feature values. After the luminance threshold values and the luminance feature values are obtained, in Step S 330 , a comparison is made between each luminance threshold value and each luminance feature value so as to determine whether CV 1 , CV 2 , CV 3  and CV 4  are larger than, smaller than or equal to the corresponding Th 1 , Th 2 , Th 3 , and Th 4 , respectively. The comparison is to determine whether the following statement is true: 
         [0000]      [( CV 1 ≧Th 1) &amp; ( CV 2 ≧Th 2) &amp; ( CV 3 ≦Th 3) &amp; ( CV 4 ≧Th 4)] 
         [0033]    The target pixel Pt is determined a noise point if the statement is true; otherwise, the target pixel Pt is determined a non-noise point. 
         [0034]    Finally, in Step  340 , the luminance value, a first chrominance value and a second chrominance value of the target pixel Pt are adjusted if the target pixel Pt is determined a noise point. The adjusted luminance value, first chrominance value and second chrominance value are expressed as: 
         [0000]        Yt _new=(1 −W 1)× Yt+W 1 ×Y _median 
         [0000]        Cbt _new=(1− W 2)× Cbt+W 2 ×Cb _median 
         [0000]        Crt _new=(1− W 3)× Crt+W 3 ×Cr _median 
         [0000]    where Yt_new, Cbt_new, Crt_new are the adjusted luminance value, first chrominance value and second chrominance value of the target pixel Pt, respectively; Ybt, Cbt and Crt are the original luminance value, first chrominance value and second chrominance value of the target pixel Pt, respectively; W1 W2 and W3 are weighting values; and Y_median, Cb_median and Cr_median are respectively a luminance median, a first chrominance median and a second chrominance median of a series [Pt, Pd 1 , Pd 2 , Pd 3 , Pd 4 , Pr 1 , Pr 2 , Pr 3 , Pr 4 ]. 
         [0035]    In Step S 350 , the luminance value, first chrominance value and second chrominance value of the target pixel Pt are remained if the target pixel Pt is determined a non-noise point. 
         [0036]    After Step  340  or Step  350 , another pixel is selected as a new target pixel, as described in Step  360 . 
         [0037]    Accordingly, through the afore-mentioned steps, the noise point in the digital image  22  can not only be identified, but also be eliminated by adjusting the luminance value and the chrominance values. 
         [0038]    Please refer to  FIG. 4 , which shows a noise reduction apparatus in accordance with one embodiment of the present invention. The noise reduction apparatus  400  can be applied in an image display such as TVs or monitors. The noise reduction apparatus  400  comprises a calculating unit  410 , a comparing unit  420 , and an adjusting unit  430 . The calculating unit  410  receives an input image Vin and calculates four luminance feature values according to a luminance value of a target pixel of the input image and the luminance values of neighboring pixels of the target pixel. The first luminance feature value is calculated by the luminance value of the target pixel and the luminance values of four neighboring pixels, where the target pixel and the four neighboring pixels form a cross shape. The second luminance feature value is calculated by the luminance value of the target pixel and the luminance values of four neighboring pixels, where the target pixel and the four neighboring pixels form an X shape. The third luminance feature value is calculated by the luminance values of the neighboring pixels. The fourth luminance feature value is calculated by the luminance value of the target pixel and a mean luminance value of the neighboring pixels. The calculating unit  410  further calculates a fourth luminance threshold value by the luminance values of the neighboring pixels of the target pixel and the mean luminance value of the neighboring pixels of the target pixel. In one embodiment, the four luminance feature values and the fourth luminance threshold value can be generated by using the equations as described above. 
         [0039]    The comparing unit  420  compares the first, second, third, and fourth luminance feature values with the first, second, third, and fourth luminance threshold values (Th 1 ˜Th 4 ), respectively, so as to determine whether the target pixel is a noise point. When the first luminance feature value is larger than the first luminance threshold value, the second luminance feature value is larger than the second luminance threshold value, the third luminance feature value is smaller than the third luminance threshold value and the fourth luminance feature value is larger than the fourth luminance threshold value, so that the target pixel is determined as a noise point. 
         [0040]    When the target pixel is determined as a noise point, the adjusting unit  430  adjusts the luminance value and the chrominance value of the target pixel. The adjusting unit  430  adjusts the luminance value of the target pixel according to a luminance median by performing a luminance weighting calculation, and the luminance median is selected from a series including the luminance value of the target pixel and the luminance values of the neighboring pixels. The detailed adjusting method of the adjusting unit  430  can be the same as mentioned above. 
         [0041]    According to the above discussion, it is apparent that the present invention discloses a noise reduction method and apparatus so as to identify noise in a digital image and adjust the luminance value and the chrominance values of a pixel that is determined a noise point so that the image quality is improved and the image distortion is avoided. 
         [0042]    Although this invention has been disclosed and illustrated with reference to particular embodiments, the principles involved are susceptible for use in numerous other embodiments that will be apparent to persons skilled in the art. This invention is, therefore, to be limited only as indicated by the scope of the appended claims.