Image denoising with color-edge contrast preserving

A color-edge contrast preserver includes a demosaicing module, a color-correcting module, a converter module and a chromatic-denoising module. The demosaicing module may demosaic a red-white-blue (RWB) pixel image of the image. The color-correcting module may color correct the demosaiced RWB pixel image and may produce a red-green-blue (RGB) pixel image from the color-corrected demosaiced RWB pixel image. The converter module to convert the RGB pixel image to a hue-saturation-value (HSV) pixel image and to generate a similarity kernel ΔY. The chromatic-denoising module may denoise a red pixel image and a blue pixel image of the RWB pixel image using the similarity kernel ΔY.

TECHNIC AL FIELD

The subject matter disclosed herein generally relates to image signal processing, and more particularly, to an apparatus and method to provide image denoising with color-edge contrast preserving.

BACKGROUND

Red-White-Blue (RWB) sensors have recently been developed and used in commercial products, such as cellphones. RWB sensors provide an advantage of for reducing low light noise (i.e., approximately +3 dB increase in SNR). A denoising technique, known as Chromatic Denoising or as Clarity+ Denoising, is used on the output of a RWB sensor. While greatly removing image noise, the denoising technique unfortunately also blurs edges across two different colors, thereby reducing color-edge contrast of the image. Other image sensors that use broadband filters, such as a color-splitter filter, may also exhibit similar problem, although not as severe.

SUMMARY

An example embodiment provides a system to preserve color-edge contrasts of an image in which the system may include a demosaicing module, a color-correcting module, a converter module and a chromatic-denoising module. The demosaicing module may demosaic a red-white-blue (RWB) pixel image of the image. The color-correcting module may color correct the demosaiced RWB pixel image and may produce a red-green-blue (RGB) pixel image from the color-corrected demosaiced RWB pixel image. The converter module to convert the RGB pixel image to a hue-saturation-value (HSV) pixel image and to generate a similarity kernel ΔY. The chromatic-denoising module may denoise a red pixel image and a blue pixel image of the RWB pixel image using the similarity kernel ΔY. In one embodiment, the similarity kernel ΔY may be:
ΔY=αΔH+βΔS+γΔV,
in which,

An example embodiment provides a method to preserve color-edge contrasts of an image in which method may include: demosaicing an RWB pixel image of the image; producing an RGB image by color correcting the demosaiced RWB pixel image; converting the RGB image to an HSV image; generating a similarity kernel ΔY from the HSV image; and de-noising a red pixel image and a blue pixel image of the RWB pixel image using the similarity kernel ΔY.

An example embodiment provides a system to preserve color-edge contrasts of an image in which the system may include a raw-image receiver, a demosaicing module, a color-correcting module, a converter module, and a chromatic-denoising module. The raw-image receiver may receive an RWB image. The demosaicing module may demosaic the RWB pixel image of the image. The color-correcting module may color correct the demosaiced RWB pixel image and to produce a RGB pixel image from the color-corrected demosaiced RWB pixel image. The converter module may convert the RGB pixel image to an HSV pixel image and to generate a similarity kernel ΔY. The chromatic-denoising module may denoise a red pixel image and a blue pixel image of the RWB pixel image using the similarity kernel ΔY.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the disclosure. It will be understood, however, by those skilled in the art that the disclosed aspects may be practiced without these specific details. In other instances, well-known methods, procedures, components and circuits have not been described in detail not to obscure the subject matter disclosed herein.

Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment disclosed herein. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” or “according to one embodiment” (or other phrases having similar import) in various places throughout this specification may not be necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In this regard, as used herein, the word “exemplary” means “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not to be construed as necessarily preferred or advantageous over other embodiments. Also, depending on the context of discussion herein, a singular term may include the corresponding plural forms and a plural term may include the corresponding singular form. It is further noted that various figures (including component diagrams) shown and discussed herein are for illustrative purpose only, and are not drawn to scale. Similarly, various waveforms and timing diagrams are shown for illustrative purpose only. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, if considered appropriate, reference numerals have been repeated among the figures to indicate corresponding and/or analogous elements.

The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting of the claimed subject matter. As used herein, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The terms “first,” “second,” etc., as used herein, are used as labels for nouns that they precede, and do not imply any type of ordering (e.g., spatial, temporal, logical, etc.) unless explicitly defined as such. Furthermore, the same reference numerals may be used across two or more figures to refer to parts, components, blocks, circuits, units, or modules having the same or similar functionality. Such usage is, however, for simplicity of illustration and ease of discussion only; it does not imply that the construction or architectural details of such components or units are the same across all embodiments or such commonly-referenced parts/modules are the only way to implement the teachings of particular embodiments disclosed herein.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this subject matter belongs. For example, the term “mod” as used herein means “modulo.” It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

As used herein, the term “module” refers to any combination of software, firmware and/or hardware configured to provide the functionality described herein in connection with a module. The term “software,” as applied to any implementation described herein, may be embodied as a software package, code and/or instruction set or instructions. The term “hardware,” as applied to any implementation described herein, may include, for example, singly or in any combination, hardwired circuitry, programmable circuitry, state-machine circuitry, and/or firmware that stores instructions executed by programmable circuitry. The modules may, collectively or individually, be embodied as software, firmware and/or hardware that forms part of a larger system, such as, but not limited to, an integrated circuit (IC), system on-chip (SoC) and so forth.

The subject matter disclosed herein provides a color-edge-preserving denoising technique that is for RWB and other broadband image sensors. That is, the subject matter disclosed herein preserves (and in some cases enhances) color-edge contrast while removing noise. In one embodiment, parameters of the color-edge-preserving denoising technique may be tuned to control the degree of color edge contrast and noise level.

FIG. 1depicts a functional block diagram of a portion of an image signal processor (ISP)100having a conventional chromatic-denoising module103. As depicted inFIG. 1, an RWB image sensor101senses an image and outputs a raw RWB pixel image110. The RWB pixel image110is received by an image preprocessing module102. The image preprocessing module102may provide some preprocessing, such as bad-pixel correction, white-balance, etc., but no demosaicing yet has been applied so each pixel contains a single color. The image preprocessing module102separates the RWB pixel image110into a red pixel image110R, a blue pixel image110B, and a white pixel image110W. The white pixel image110W is reconstructed and demosaiced, which also may be referred to as a Luma channel (Y).

The red pixel image110R, the blue pixel image110B, and the white pixel image110W are received by the conventional chromatic-denoising module103. The reconstructed white channel W is subtracted from both the red pixel image110R and the blue pixel image110B to respectively form a red pixel image111R and a blue pixel image111B. A non-local means (NLM) process denoises both the red pixel image111R and the blue pixel image111B using the reconstructed white channel W to respectively form a red channel112R and a blue channel112B. The reconstructed white channel W is then added to both the red channel112R and the blue channel112B to respectively form a red channel113R and a blue channel113B. Both the red channel113R and the blue channel113B are demosaiced using the reconstructed white channel W to respectively form a chromatically denoised red channel114R and a chromatically denoised blue channel114B. The reconstructed white channel W is then used to form a chromatically denoised RWB pixel image115. The conventional chromatic-denoising module103removes a significant amount of noise, but also blurs edges across two different colors so that color-edge contrast of the image has been reduced.

FIG. 2depicts a functional block diagram of a portion of an ISP200having a chromatic-denoising module203and a color-contrast preserving module204according to the subject matter disclosed herein. It should be noted that the image preprocessing module202, the chromatic-denoising module203, and the color-contrast preserving module204may, collectively or individually, be embodied as software, firmware and/or hardware that forms part of a larger system, such as, but not limited to, an IC, SoC and so forth.FIG. 3depicts a flow diagram of an example embodiment of a method300to denoise a RWB pixel image while preserving color-contrast according to the subject matter disclosed herein.

As depicted inFIG. 2, an RWB image sensor201senses an image and outputs a raw (unprocessed) RWB pixel image210. The RWB pixel image210is received by an image preprocessing module202. The image preprocessing module202may provide some preprocessing, such as bad-pixel correction, white-balance, etc., but no demosaicing has yet been applied so each pixel contains a single color. The image preprocessing module202separates the RWB pixel image210into a red pixel image210R, a blue pixel image210B, and a white pixel image210W. At301inFIG. 3, the image denoising with color-edge contrast preserving process disclosed herein begins. At302inFIG. 3, the white pixel image210W is reconstructed and demosaiced at303. The reconstructed white pixel image210W may also be referred to as a Luma channel (Y).

At304, the reconstructed and demosaiced white channel W is color corrected by the color-contrast preserving module204to form a RGB pixel image220. At305, the RGB pixel image220is transformed from the RGB color space to become a hue-saturation-value (HSV) pixel image221. The HSV pixel image is used to determine a similarity kernel ΔY at306. The similarity kernel ΔY will be used by the chromatic-denoising module203instead of the reconstructed white channel during a NLM process during the chromatic denoising.

In one embodiment, the similarity kernel ΔY is determined as
ΔY=αΔH+βΔS+γΔV,(1)
in which,

As indicated by Equation (1), the variables α, β and γ are linearly related by the constraint α+β+γ=1. There are two general cases for which the values for the coefficients α, β and γ may be simply defined. In the first case, α=β=0.5, and γ=0. In this case, the color edges are preserved and would normally be used. In the second case, α=β=0, and γ=1. In this case, the color edge preservation is disabled and would be used for a low-lighting situation.

Referring back toFIG. 2, the red pixel image210R, the blue pixel image210B, and the white pixel image210W are received by the chromatic-denoising module203. At307inFIG. 3, the chromatic-denoising module203subtracts the white channel W from both the red pixel image210R and the blue pixel image210B to respectively form a red pixel image211R and a blue pixel image211B′. At308, an NLM process uses the similarity kernel ΔY is used to denoise both the red pixel image211R′ and the blue pixel image211B′ to respectively form a red channel211R′ and a blue channel211B′. At309, the reconstructed white channel W is then added to both the red channel211R′ and the blue channel211B′ to respectively form a red channel211R″ and a blue channel211B″. Both the red channel211R″ and the blue channel211B″ are demosaiced using the reconstructed white channel W to respectively form a chromatically denoised red channel211R″ and a chromatically denoised blue channel211B″. At310, the reconstructed white channel W is then used to output a chromatically denoised R″WB″ pixel image215. The process ends at311.

FIG. 4depicts an electronic device400that comprises one or more integrated circuits (chips) comprising an image denoiser with color-edge contrast preservation according to the subject matter disclosed herein. Electronic device400may be used in, but not limited to, a computing device, a personal digital assistant (PDA), a laptop computer, a mobile computer, a web tablet, a wireless phone, a cell phone, a smart phone, a digital music player, or a wireline or wireless electronic device. The electronic device400may comprise a controller410, an input/output device420such as, but not limited to, a keypad, a keyboard, a display, a touch-screen display, a camera, and/or an image sensor, a memory430, and an interface440that are coupled to each other through a bus450. The controller410may comprise, for example, at least one microprocessor, at least one digital signal process, at least one microcontroller, or the like. The memory430may be configured to store a command code to be used by the controller410or a user data. Electronic device400and the various system components comprising electronic device400may comprise an image denoiser with color-edge contrast preservation according to the subject matter disclosed herein. The interface440may be configured to include a wireless interface that is configured to transmit data to or receive data from a wireless communication network using a RF signal. The wireless interface440may include, for example, an antenna, a wireless transceiver and so on. The electronic system400also may be used in a communication interface protocol of a communication system, such as, but not limited to, Code Division Multiple Access (CDMA), Global System for Mobile Communications (GSM), North American Digital Communications (NADC), Extended Time Division Multiple Access (E-TDMA), Wideband CDMA (WCDMA), CDMA2000, Wi-Fi, Municipal Wi-Fi (Muni Wi-Fi), Bluetooth, Digital Enhanced Cordless Telecommunications (DECT), Wireless Universal Serial Bus (Wireless USB), Fast low-latency access with seamless handoff Orthogonal Frequency Division Multiplexing (Flash-OFDM), IEEE 802.20, General Packet Radio Service (GPRS), iBurst, Wireless Broadband (WiBro), WiMAX, WiMAX-Advanced, Universal Mobile Telecommunication Service-Time Division Duplex (UMTS-TDD), High Speed Packet Access (HSPA), Evolution Data Optimized (EVDO), Long Term Evolution-Advanced (LTE-Advanced), Multichannel Multipoint Distribution Service (MMDS), and so forth.