IP Library › Granted Patent US 12,182,963
Granted Patent B2
US 12,182,963 · App. 17/458,699 · Granted Dec 31, 2024

Image processing apparatus and method implementing a neural network to pre-process a CFM image for further process by ISP pipeline

Inventors: Nickolay Dmitrievich Egorov (Saint, RU); Elena Alexandrovna Alshina (Munich, DE); Marat Ravilevich Gilmutdinov (Saint, RU); Dmitry Vadimovich Novikov (Saint, RU); Anton Igorevich Veselov (Saint, RU); Kirill Aleksandrovich Malakhov (Saint, RU)
Assignee: Huawei Technologies Co., Ltd.
G06T3/4015G06N3/08G06T5/70G06T5/73G06T5/90G06T2207/10144G06T2207/20081G06T2207/20084
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Quick Facts
Patent No.
US 12,182,963
App. No.
17/458,699
Granted
Dec 31, 2024
Kind
B2
Abstract

An image processing apparatus processes a color filter mosaic, CFM, image of a scene into a final image of the scene. The image processing apparatus includes processing circuitry configured to implement a neural network. The neural network is configured to process the CFM image into an enhanced CFM image. The processing circuitry is further configured to transform the enhanced CFM image into the final image.

Claims (15)

1. An image processing apparatus for processing an original color filter mosaic (CFM) image of a scene into a final image of the scene, the image processing apparatus comprising processing circuitry configured to:

implement a neural network and process the original CFM image into an enhanced CFM image using the neural network, the original CFM image and the enhanced CFM image corresponding to a same CFM, wherein the neural network is implemented as a pre-processing stage prior to and independent of an image signal processing (ISP) pipeline, so that no retraining of the neural network is required in case of modifications of the ISP pipeline, and

transform, by applying the ISP pipeline, the enhanced CFM image into the final image.

2. The image processing apparatus of claim 1 , wherein the CFM is one of the following: a Bayer filter mosaic, a red green blue emerald (RGBE) filter mosaic, a cyan yellow yellow magenta (CYYM) filter mosaic, a cyan yellow green magenta (CYGM) filter mosaic, or an X-Trans filter mosaic.

3. The image processing apparatus of claim 2 , wherein the transforming, by applying the ISP pipeline, the enhanced CFM image into the final image comprises de-mosaicing.

4. The image processing apparatus of claim 1 , wherein each or both of the processing the original CFM image into the enhanced CFM image and the transforming, by applying the ISP pipeline, the enhanced CFM image into the final image comprises one or more of the following: denoising, white-balancing, tone mapping, contrast enhancement, or sharpening.

5. The image processing apparatus of claim 1 , wherein the image processing apparatus further comprises an image capturing device configured to generate the original CFM image of the scene.

6. The image processing apparatus of claim 1 , wherein each of the original CFM image and the enhanced CFM image comprises a plurality of samples correspond to a plurality of color channels, and wherein the pattern of the plurality of samples and the number of the plurality of color channels associated with the original CFM image are the same as those of the enhanced CFM image.

7. The image processing apparatus of claim 1 , wherein the neural network remains the same in response to a modification to the ISP pipeline.

8. An image processing method for processing an original color filter mosaic (CFM) image of a scene into a final image of the scene, the method comprising:

processing the original CFM image into an enhanced CFM image using a neural network, wherein the neural network is implemented as a pre-processing stage prior to and independent of an image signal processing (ISP) pipeline, so that no retraining of the neural network is required in case of modifications of the ISP pipeline; and

transforming, by applying the ISP pipeline, the enhanced CFM image into the final image.

9. A non-transitory computer-readable storage medium carrying program code which causes a computer or a processor to perform the method of claim 8 when the program code is executed by the computer or the processor.

10. The method of claim 8 , wherein each of the original CFM image and the enhanced CFM image comprises a plurality of samples correspond to a plurality of color channels, and wherein the pattern of the plurality of samples and the number of the plurality of color channels associated with the original CFM image are the same as those of the enhanced CFM image.

11. The method of claim 8 , wherein the neural network remains the same in response to a modification to the ISP pipeline.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 21, 2024
From: EGOROV, NICKOLAY DMITRIEVICH; ALSHINA, ELENA ALEXANDROVNA; GILMUTDINOV, MARAT RAVILEVICH; NOVIKOV, DMITRY VADIMOVICH; VESELOV, ANTON IGOREVICH; MALAKHOV, KIRILL ALEKSANDROVICH
To: HUAWEI TECHNOLOGIES CO., LTD.
Reel/Frame 067480/0920 →
Continuity (2)
Continuation PCTRU2019000131 · Feb 27, 2019
Related Publication 20210390658A1 · Dec 16, 2021