Apparatus and method for adaptively reducing noise in a noisy input image signal

An adaptive apparatus for spatially reducing noise in a noisy input image signal comprising:

• a plurality of parallel-connected adaptive spatial noise reducers each presenting a distinct set of predetermined pixels-window characteristics, each said noise reducer receiving said noisy input image signal to generate a corresponding pre-filtered output image signal and an averaging unit receiving each said pre-filtered output image signal at a corresponding positive input thereof to generate a noise-filtered output image signal, wherein each said noise reducer comprises:
• a low-pass filter receiving said noisy input image signal to generate a noisy low-spatial frequency image signal;
• a first pixel-based serial-to-parallel converter receiving the noisy low-spatial frequency image signal to generate a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to the set of predetermined pixels-window characteristics;
• a pixel-based local window segmentation processor comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• a counter generating a selected-pixels count signal;
• a second pixel-based serial-to-parallel converter receiving the noisy input image signal to generate a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• a mean estimator combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• a minimum-mean-square-error filter receiving the noisy input image parallel signals, the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate said pre-filtered output image signal according to an input noise statistic signal.

An adaptive apparatus for spatially reducing noise in a noisy input image signal comprising:

• a low-pass filter receiving said noisy input image signal to generate a noisy low-spatial frequency image signal;
• a plurality of parallel-connected adaptive spatial noise reducers each presenting a distinct set of predetermined pixels-window characteristics, each said noise reducer receiving said noisy low-spatial frequency image signal to generate a corresponding pre-filtered output image signal and an averaging unit receiving each said pre-filtered output image signal at a corresponding positive input thereof to generate a noise-filtered output image signal, wherein each said noise reducer comprises:
• a first pixel-based serial-to-parallel converter receiving the noisy low-spatial frequency image signal to generate a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to said set of predetermined pixels-window characteristics;
• a pixel-based local window segmentation processor comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• a counter generating a selected-pixels count signal;
• a second pixel-based serial-to-parallel converter receiving the noisy input image signal to generate a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• a mean estimator combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• a minimum-mean-square-error filter receiving the noisy input image parallel signals, the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate said pre-filtered output image signal according to an input noise statistic signal.

An adaptive apparatus for spatially reducing noise in a noisy input image signal comprising:

• an adaptive spatial noise reducer including:
• a low-pass filter receiving said noisy input image signal to generate a noisy low-spatial frequency image signal;
• a first pixel-based serial-to-parallel converter receiving the noisy low-spatial frequency image signal to generate a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to a set of predetermined pixels-window characteristics;
• a pixel-based local window segmentation processor comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• a counter generating a selected-pixels count signal;
• a second pixel-based serial-to-parallel converter receiving the noisy input image signal to generate a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• a mean estimator combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• a minimum-mean-square-error filter receiving the noisy input image parallel signals, the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate a noise-filtered output image signal according to an input noise statistic signal;
• and
• a controllable noise statistic estimator including:
• a high-pass two-dimensional filter receiving the noisy input image signal to generate a noisy horizontal/vertical high-spatial frequency image signal;
• a third pixel-based serial-to-parallel converter receiving the noisy horizontal/vertical high-spatial frequency image signal to generate a group of noisy horizontal/vertical high-spatial frequency image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• a statistic calculator combining the noisy horizontal/vertical high-spatial frequency image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a resulting noise statistic signal associated with the locally considered pixel;
• a noise statistic estimator unit generating said input noise statistic signal from the resulting noise statistic signal.

An adaptive method for spatially reducing noise in a noisy input image signal comprising the steps of:

• i) filtering said noisy input image signal to generate a noisy low-spatial frequency image signal;
• ii) converting the noisy low-spatial frequency image signal to a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to a set of predetermined pixels-window characteristics;
• iii) comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• iv) generating a selected-pixels count signal;
• v) converting the noisy input image signal to a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• vi) combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• and
• vii) processing the noisy input image parallel signals with a minimum-mean-square-error filter using the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate a noise-filtered output image signal according to an input noise statistic signal.

An adaptive method for spatially reducing noise in a noisy input image signal comprising the steps of:

• i) filtering said noisy input image signal to generate a noisy low-spatial frequency image signal;
• ii) converting the noisy low-spatial frequency image signal to a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to a set of predetermined pixels-window characteristics;
• iii) comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• iv) generating a selected-pixels count signal;
• v) converting the noisy input image signal to a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• vi) combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• vii) processing the noisy input image parallel signals with a minimum-mean-square-error filter using the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate a pre-filtered output image signal according to an input noise statistic signal;
• viii) repeating said steps ii) to vii) according to at least one further complementary set of pixels-window characteristics to generate a further pre-filtered output image signal according to the input noise statistic signal;
• and
• ix) averaging said output image signals to generate a noise-filtered output image signal.

An adaptive method for spatially reducing noise in a noisy input image signal comprising:

• i) filtering said noisy input image signal to generate a noisy low-spatial frequency image signal;
• ii) converting the noisy low-spatial frequency image signal to a group of noisy low-spatial frequency image parallel signals associated with a locally considered pixel and according to a set of predetermined pixels-window characteristics;
• iii) comparing values of the noisy low-spatial frequency image parallel signals associated with pixels included within the window with the locally considered pixel value to generate segmented local window parallel signals associated with selected pixels;
• iv) generating a selected-pixels count signal;
• v) converting the noisy input image signal to a group of noisy input image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• vi) combining the noisy input image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a mean pixel value signal associated with the locally considered pixel;
• vii) filtering the noisy input image signal to generate a noisy horizontal/vertical high-spatial frequency image signal;
• viii) converting the noisy horizontal/vertical high-spatial frequency image signal to a group of noisy horizontal/vertical high-spatial frequency image parallel signals associated with the locally considered pixel and according to the set of predetermined pixels-window characteristics;
• ix) combining the noisy horizontal/vertical high-spatial frequency image parallel signals with the segmented local window parallel signals and the selected-pixels count signal to generate a resulting noise statistic signal associated with the locally considered pixel;
• x) generating an input noise statistic signal from the resulting noise statistic signal;
• and
• xi) processing the noisy input image parallel signals with a minimum-mean-square-error filter using the segmented local window parallel signals, the selected-pixels count signal and the mean pixel value signal to generate a noise-filtered output image signal according to the input noise statistic signal.