Apparatus and method for smoothing images

• US 5,442,462 A
• Filed: 06/10/1992
• Issued: 08/15/1995
• Est. Priority Date: 06/10/1992
• Status: Expired due to Term

• Current Assignee: DVP Technologies Limited 18 Hatzouk Street
• Original Assignee: DVP Technologies Ltd.
• Inventors: Guissin, Rami
• Primary Examiner(s): IP, SHIK LUEN PAUL
• Application Number:
  US07/896,682
• Time in Patent Office: 1,161 Days
• Field of Search: 358/445, 358/446, 358/464, 358/447, 358/463, 358/455, 358/457, 358/294, 358/456, 358/465, 358/298, 358/296, 358/280, 358/282, 358/261.3, 364/521, 382/22, 382/54, 382/27, 382/41, 382/50, 382/49, 340/728
• US Class Current: 358/463
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

Apparatus for image noise reduction which employs an adaptive, acuity-preserving, multi-directional and multi dimensional smoothing method. The method and apparatus of the present invention are applicable, inter alia, for (a) adaptive spatial noise reduction in still images, (b) adaptive temporal noise reduction in time changing image sequences, and (c) adaptive spatio-temporal noise reduction by combining the first two approaches (a) and (b).

Claims

1. Apparatus for one-directional time domain smoothing of a current image which was preceded by a sequence of images, the apparatus comprising:

apparatus for computing a difference function between the raw value of an individual pixel of the current image and a smoothed preceding image value corresponding to at least one pixels of at least one preceding image; and

apparatus for generating a smoothed pixel value for the individual pixel of the current image by computing a weighted sum of the smoothed preceding image value and of the raw value of the individual pixel of the current image wherein the weights are a function of said difference function and of at least one characteristic of at least a portion of the current image other than the difference between the individual pixel value and at least one pixels of at least one preceding image.

2. A method for one-directional time domain smoothing of a current image which was preceded by a sequence of images, the method comprising:

computing a difference function between the raw value of an individual pixel of the current image and a smoothed preceding image value corresponding to at least one pixels of at least one preceding image; and

generating a smoothed preceding image pixel value for the individual pixel of the current image by computing a weighted sum of the smoothed value and of the raw value of the individual pixel of the current image wherein the weights are a function of said difference function and of at least one characteristic of at least a portion of the current image other than the difference between the individual pixel value and at least one pixels of at least one preceding image.

3. A method according to claim 2 wherein said at least one characteristic comprises the location of boundaries of blocks employed for block transform image coding.

4. A method according to claim 2 wherein said at least one characteristic comprises a local average of image brightness.

5. A method according to claim 2 and also comprising:

storing the current image; and

generating a smoothed pixel value for at least one individual pixel in the current image based on;

at least one smoothed pixel value of said current image; and

at least a portion of an image following said current image in a temporal sequence.

6. A method according to claim 5 and also comprising spatially smoothing the following image and wherein the smoothed current image pixel value is based on at least one spatially smoothed portion of said following image.

7. A method for acuity-preserving image smoothing comprising:

proceeding along at least a portion of a first dimension of received image pixels in a first direction and recursively computing a first sequence of estimated pixel values from the received image pixels defined along the first direction;

proceeding along at least a portion of the first dimension of received image pixels in a second direction and recursively computing a second sequence of estimated pixel values from the received image pixels defined along the second direction; and

for at least one individual pixel along the first dimension, computing an improved estimated pixel value for the individual pixel based on a data dependent combination of at least estimated pixel values in the first and second sequences.

8. A method according to claim 7 wherein, for an individual pixel in the first sequence, said proceeding and computing comprises:

computing a difference value between the received image pixel and an adjacently preceding estimated pixel value in the first sequence;

employing at least the received image pixel and at least one preceding estimated pixel values in the first sequence to estimate a first directional signal to noise ratio;

generating an adjusted difference value to reflect the first directional signal to noise ratio; and

employing the adjusted difference value to update an adjacently preceding estimated pixel value, thereby to compute the estimated pixel value of the individual pixel.

9. A method according to claim 8 wherein the signal to noise ratio depends on locally weighted signal to noise ratio estimates of at least one pixel in the vicinity of the individual pixel.

10. A method according to claim 9 wherein the vicinity is included within a coding block boundary.

11. A method according to claim 7 wherein said computing an estimated pixel value comprises:

computing a difference value between the received image pixel and a function of at least adjacently preceding estimated pixel values in the first and second sequences;

employing preceding estimated pixel values in the first and second sequences to estimate a two-directional signal to noise ratio;

adjusting the difference value to reflect the signal to noise ratio; and

employing the adjusted difference value to update a function of at least adjacently preceding estimated pixel values in the first and second sequences, thereby to compute the improved estimated pixel value of the individual pixel.

12. A method according to claim 11 wherein the signal to noise ratio depends on locally weighted signal to noise ratio estimates of at least one pixel in the vicinity of the individual pixel.

13. A method according to claim 7 wherein the received image pixels comprise estimated pixel values and each individual estimated pixel value is computed by combining at least three previous estimated pixel values arranged along three respective dimensions relative to the individual estimated pixel value.

14. A method according to claim 7 and also comprising:

repeating, for at least a second dimension of received image pixels, said proceeding in first and second directions and said computing an improved estimated pixel value, thereby to compute at least one additional improved estimated pixel value for each individual pixel; and

combining the at least two improved estimated pixel values, thereby to obtain a further improved at least two-dimensional estimated pixel value.

15. A method according to claim 7 and also comprising:

performing the proceeding and the improved estimated pixel value computation at least once more, using a second dimension as said first dimension.

16. A method according to claim 15 and also comprising:

adjusting outputs of the proceeding using the second dimension and of the improved estimated pixel value computation using the second dimension in order to reflect the difference between the received image and outputs of the proceeding using the first dimension and of the improved estimated pixel value computation using the first dimension.

17. A method according to claim 7 wherein the received image defines a second dimension thereof and a scanning direction in which the image is received along the second dimension, the method also comprising:

proceeding along at least a portion of the second dimension of received image pixels in the scanned direction and computing a sequence of second dimension estimated pixel values from the improved estimated pixel values of the first dimension; and

for each individual pixel along the second dimension, comparing an adjacently preceding second dimension estimated pixel value in the sequence of second dimension estimated pixel values and an improved estimated pixel value of the first dimension which adjacently proceeds the individual pixel along the second dimension, thereby to compute a further improved estimated pixel value for the individual pixel.

18. A method according to claim 17 and also comprising:

adjusting outputs of the proceeding using the second dimension and of the improved estimated pixel value computation using the second dimension in order to reflect the difference between the received image and outputs of the proceeding using the first dimension and of the improved estimated pixel value computation using the first dimension.

19. A method according to claim 7 and also comprising:

adjusting outputs of each estimated pixel value computation to preserve narrow elongated contours.

20. A method according to claim 7 wherein said first dimension comprises a temporal dimension.

21. A method according to claim 7 wherein said first dimension comprises a spatial dimension.

22. A method according to claim 7 and also comprising imaging an image using an electronic imager, thereby to define the received image pixels.

23. A method according to claim 7 and also comprising scanning an image using an electronic scanner, thereby to define the received image pixels.

24. A method according to claim 7 and also comprising receiving said received image pixels from a video system.

25. A method according to claim 7 wherein recursively computing the first sequence comprises computing at least one data dependent combination of received image pixels.

26. A method according to claim 25 wherein recursively computing the second sequence comprises computing at least one data dependent combination of received image pixels.

27. A method according to claim 7 wherein said data dependent combination comprises an image-dependent weighted sum in which the weights depend on at least a portion of the image.

28. A method according to claim 7 wherein said data on which said combination depends comprises the location of boundaries of blocks employed for block transform image coding.

29. A method according to claim 7 wherein said data on which said combination depends comprises a local average of image brightness.

30. Apparatus for acuity-preserving image smoothing comprising:

a first-direction recursive pixel value estimator operative to proceed along at least a portion of a first dimension of received image pixels in a first direction and to recursively compute a first sequence of estimated pixel values from the received image pixels defined along the first direction;

a second-direction recursive pixel value estimator operative to proceed along at least a portion of the first dimension of received image pixels in a second direction and to recursively compute a second sequence of estimated pixel values from the received image pixels defined along the second direction; and

a data dependent pixel value estimator operative, for at least one individual pixel along the first dimension, to compute an improved estimated pixel value for the individual pixel based on a data dependent combination of at least estimated pixel values in the first and second sequences.

31. Apparatus according to claim 30 wherein, for an individual pixel in the first sequence, said first-direction pixel value estimator comprises:

an estimate-received value difference computer operative to compute a difference value between the received image pixel and an adjacently preceding estimated pixel value in the first sequence;

an SNR ratio estimator operative to employ at least the received image pixel and at least one preceding estimated pixel values in the first sequence to estimate a first directional signal to noise ratio;

a difference adjuster operative to generate an adjusted difference value to reflect the first directional signal to noise ratio; and

a pixel value estimator operative to employ the adjusted difference value to update an adjacently preceding estimated pixel value, thereby to compute the estimated pixel value of the individual pixel.

32. Apparatus according to claim 30 wherein said data dependent pixel value estimator comprises:

an estimate-received value difference computer operative to compute a difference value between the received image pixel and a function of at least adjacently preceding estimated pixel values in the first and second sequences;

an SNR ratio estimator operative to employ preceding estimated pixel values in the first and second sequences to estimate a two-directional signal to noise ratio;

a difference adjuster operative to adjust the difference value to reflect the signal to noise ratio; and

a pixel value estimator operative to employ the adjusted difference value to update a function of at least adjacently preceding estimated pixel values in the first and second sequences, thereby to compute the improved estimated pixel value of the individual pixel.