Image noise measurement system and method

1. An image noise measurement system, which performs a noise estimation on an image, comprising:

a storage device, storing a previous image prior to the image;

a noise estimator, connected to the storage device, for performing a noise estimation on sub-areas of the image and the previous image and producing a noise estimation index for the sub-area of the image;

a distribution calculator, connected to the noise estimator, for calculating a distribution of positive and negative signs of pixel differences in the sub-areas of the image and the previous image that are covered by the noise estimator and outputting a positive sign number and a negative sign number;

a confidence generator, connected to the distribution calculator, for producing a confident level index according to the positive sign number and the negative sign number; and

a recursive filter, connected to the noise estimator and the confidence generator, for performing a recursive filtering operation on the noise estimation index according to the confident level index so as to produce a noise estimate for the image;

wherein the noise estimation index is expressed as:

∑

i

,

j

⁢

⁢



P

N

⁡

(

i

,

j

)

-

P

N

-

1

⁡

(

i

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j

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,

wherein i, j indicated the sub-areas covered by the noise estimator respectively, P N (i,j) indicates a pixel of the sub-area of the image covered by the noise estimator, and P N-1 (i,j) indicates a pixel of the sub-area of the previous image covered by the noise estimator; and

wherein the distribution calculator comprises:

a first comparator, having a first input terminal to receive the pixel P N (i,j) and a second input terminal to receive the pixel P N-1 (i,j) and producing a first trigger signal when the pixel P N (i,j) is greater than the pixel P N-1 (i,j); and

a first counter, connected to the first comparator for counting the positive sign number according to the first trigger signal.

2. The system as claimed in claim 1 , wherein the distribution calculator further comprises:

a second comparator, having a first input terminal to receive the pixel P N (i,j) and a second input terminal to receive the pixel P N-1 (i,j) and producing a second trigger signal when the pixel P N (i,j) is smaller than the pixel P N-1 (i,j); and

a second counter, connected to the second comparator for counting the negative sign number according to the second trigger signal.

3. The system as claimed in claim 2 , wherein the confident level index produced by the confidence generator is expressed as:

1−{|No(+)−No(−)|/total_no},

wherein No(+) indicates the positive sign number, No(−) indicates the negative sign number, and total_no indicates a total number of pixels of one sub-area covered by the noise estimator.

4. The system as claimed in claim 3 , wherein the confidence generator further produces a complementary confident level index which is expressed as:

|No(+)−No(−)|/total_no,

wherein No(+) indicates the positive sign number, No(−) indicates the negative sign number, and total_no indicates the total number of pixels of the one sub-area covered by the noise estimator.

5. The system as claimed in claim 4 , wherein the recursive filter comprises:

a first multiplier, connected to the confidence generator and the noise estimator, having a first input terminal to receive the noise estimation index and a second input terminal to receive the confident level index to accordingly multiply the noise estimation index by the confident level index so as to produce an adjustment noise index;

an adder, connected to the first multiplier, having a first input terminal to receive the adjustment noise index and a second input terminal to receive a feedback adjustment estimate;

a register, connected to the adder for registering an output of the adder and producing the noise estimate; and

a second multiplier, connected to the confidence generator and the register, having a first input terminal to receive the complementary confident level index and a second input terminal to receive the noise estimate to accordingly multiply the noise estimate by the complementary confident level index so as to produce the feedback adjustment estimate.

6. A method of measuring an image noise, which performs a noise estimation on an image, the method comprising:

storing a previous image immediately prior to the image;

performing a noise estimation on sub-areas of the image and the previous image and producing a noise estimation index for the sub-area of the image;

calculating a distribution of positive and negative signs of pixel differences in the sub-areas of the image and the previous image and outputting a positive sign number and a negative sign number;

producing a confident level index according to the positive sign number and the negative sign number; and

performing a recursive filtering operation on the noise estimation index according to the confident level index so as to produce a noise estimate for the image;

wherein the noise estimation index is expressed as:

∑

i

,

j

⁢

⁢



P

N

⁡

(

i

,

j

)

-

P

N

-

1

⁡

(

i

,

j

)



,

wherein i, j indicated the sub-areas covered by the noise estimator respectively, P N (i,j) indicates a pixel of the sub-area of the image covered by the noise estimator, and P N-1 (i,j) indicates a pixel of the sub-area of the previous image covered by the noise estimator; and

wherein the step of calculating a distribution of positive and negative signs of pixel differences comprises:

produces a first trigger signal when the pixel P N (i,j) is greater than pixel P N-1 (i,j); and

counting the positive sign number according to the first trigger signal.

7. The method as claimed in claim 6 , further comprising:

producing a second trigger signal when the pixel P N (i,j) is smaller than the pixel P N-1 (i,j); and

counting the negative sign number according to the second trigger signal.

8. The method as claimed in claim 7 , wherein the confident level index is expressed as:

1−{|No(+)−No(−)|/total_no},

wherein No(+) indicates the positive sign number, No(−) indicates the negative sign number, and total_no indicates a total number of pixels of the sub-area of the image covered by the noise estimator.

9. The method as claimed in claim 8 , wherein the step of producing a confident level index further produces a complementary confident level index which is expressed as:

|No(+)−No(−)|/total_no,

wherein No(+) indicates the positive sign number, No(−) indicates the negative sign number, and total_no indicates the total number of pixels of the sub-area of the image covered by the noise estimator.

10. The method as claimed in claim 9 , wherein the step of performing a recursive filtering operation comprises:

receiving the noise estimation index and the confident level index so as to multiply the noise estimation index and the confident level index to produce an adjustment noise index;

receiving the adjustment noise index and a feedback adjustment estimate and producing an output;

registering the output and producing the noise estimate; and

receiving the complementary confident level index and the noise estimate so as to multiply the noise estimation index and the confident level index to produce the feedback adjustment estimate.