WO2011121165A1 - Image sensor optimization - Google Patents
Image sensor optimization Download PDFInfo
- Publication number
- WO2011121165A1 WO2011121165A1 PCT/FI2010/050243 FI2010050243W WO2011121165A1 WO 2011121165 A1 WO2011121165 A1 WO 2011121165A1 FI 2010050243 W FI2010050243 W FI 2010050243W WO 2011121165 A1 WO2011121165 A1 WO 2011121165A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- saturation signal
- photodetectors
- optimized saturation
- locally
- areas
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
- H04N9/643—Hue control means, e.g. flesh tone control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/50—Control of the SSIS exposure
- H04N25/57—Control of the dynamic range
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
- H04N25/61—Noise processing, e.g. detecting, correcting, reducing or removing noise the noise originating only from the lens unit, e.g. flare, shading, vignetting or "cos4"
-
- H—ELECTRICITY
- H10—SEMICONDUCTOR DEVICES; ELECTRIC SOLID-STATE DEVICES NOT OTHERWISE PROVIDED FOR
- H10F—INORGANIC SEMICONDUCTOR DEVICES SENSITIVE TO INFRARED RADIATION, LIGHT, ELECTROMAGNETIC RADIATION OF SHORTER WAVELENGTH OR CORPUSCULAR RADIATION
- H10F39/00—Integrated devices, or assemblies of multiple devices, comprising at least one element covered by group H10F30/00, e.g. radiation detectors comprising photodiode arrays
- H10F39/80—Constructional details of image sensors
- H10F39/802—Geometry or disposition of elements in pixels, e.g. address-lines or gate electrodes
- H10F39/8023—Disposition of the elements in pixels, e.g. smaller elements in the centre of the imager compared to larger elements at the periphery
Definitions
- the present invention generally relates to digital photography and image sensor optimization and more particularly, but not exclusively to full well capacity optimization.
- full well capacity can be defined as the maximum signal or number of electrons that each pixel can hold before saturating. This has an effect on dynamic range of image sensor.
- One of the decisions that has to be made when designing an image sensor is the trade off between full well capacity, performance in low light conditions (conversion gain: how high signal voltage each electron generates) and density of defect pixels. The higher voltage is applied to a pixel, the higher full well capacity can be achieved. However, higher voltage may increase the defect density of the pixels.
- an apparatus comprising:
- the photodetectors are configured to use locally optimized saturation signal.
- an apparatus comprising:
- At least one memory including computer program code
- the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform:
- a computer program embodied on a computer readable medium comprising computer executable program code which, when executed by at least one processor of an apparatus, causes the apparatus to perform:
- Fig. 1A illustrates an example of global saturation signal optimization according to an example embodiment
- Fig. 1 B illustrates an example of local saturation signal optimization according to an example embodiment
- Fig. 2 shows a flow chart according to an example embodiment
- Fig. 3A shows a flow chart according to an example embodiment
- Fig. 3B shows a flow chart according to an example embodiment
- Fig. 4 shows a block diagram of an apparatus according to an example embodiment
- Fig. 5 shows a block diagram of a sensor according to an example embodiment.
- photogate based pixels are employed.
- the photogates allow each pixel of an image sensor to be driven with their own driving voltage. This allows pixel-wise optimization of saturation signal and full well capacity, for example. It must be noted that photogates are just one example and other embodiments may use some other type of photodetectors or light detecting elements.
- image sensor pixel parameters are optimized over the image sensor plane.
- sensor full well capacity /saturation signal is optimized over the image plane/image sensor area so that it corresponds to typical camera behaviour where the system relative illumination gradually drops from the image center towards the corners of the image plane.
- FIG. 1A illustrates an example of global saturation signal optimization according to an example embodiment.
- Dashed line 1 1 shows maximum signal (full well capacity) as a function of distance from image center and solid line 12 shows exposure level as a function of distance from image center.
- the maximum signal is constant over the image plane.
- the main optical reasons for decreasing relative illumination are optical cosine law and vignetting.
- the main sensor-related reason is the fact that the sensor response decreases when light rays arrive at the sensor surface in a higher angle.
- Figure 1 B illustrates an example of local saturation signal optimization according to an example embodiment.
- Dashed line 15 shows maximum signal (full well capacity) as a function of distance from image center and solid line 16 shows exposure level as a function of distance from image center.
- the maximum signal is optimized separately for different parts of the image plane so that the maximum signal is higher at the image center than in corners (i.e. when distance from the image center increases).
- the center and corner areas of the sensor saturate at the exposure when using the sensor with a practical lens. In this way, higher exposure level can be achieved over the image plane when compared to the example in Figure 1A. Additionally noisy image corners caused by poor relative illumination may be avoided or at least reduced.
- Figure 2 shows a flow chart illustrating local saturation signal optimization according to an example embodiment.
- image plane is divided into a plurality of subblocks or areas.
- a subblock comprises one pixel.
- Alternative a subblock may comprise more than one pixel, e.g. four pixels.
- saturation signal optimization is performed separately for each subblock or area such that saturation signal in different areas is independent from saturation signal in other areas.
- the locally optimized saturation signal is such that saturation signal in a center part of the image plane is higher than saturation signal in corners areas of the image plane.
- the system switches between global and local saturation signal optimization depending on current image capturing conditions.
- the image capturing condition may be illumination condition or exposure condition, for example.
- Figure 3A shows a flow chart according to such example embodiment. In phase 31 image capturing condition is determined.
- determination of the image capturing condition is done so that all cases which do not need gain are considered have "bright light illumination condition" and all other cases are considered have “low light illumination condition”. Also other methods or criteria may be used.
- low light condition globally optimized saturation signal is used in phase 32.
- bright light condition locally optimized saturation signal is used in phase 33. E.g. when going from bright light to low light, the system switches from global saturation signal optimization to local saturation signal optimization and vice versa.
- the local and global saturation signals may be for example similar to the ones illustrated in Figure 1 A and 1 B. It is to be noted that this is just an example and other alternatives may exist.
- FIG. 3B shows a flow chart according to such example embodiment.
- phase 35 changing image capturing condition is detected, and in phase 36, the system changes gradually between locally and globally optimized saturation signal.
- An advantage obtained by local saturation signal optimization is that signal-to- noise ratio can be improved in image corners instead of correcting only brightness. In this way better image quality and better trade-off between dark current and full well capacity may be obtained.
- saturation signal is optimized locally, the exposure level over the image plane (or sensor size) can be optimized for both saturation signal and for vignetting/shading reduction.
- Defect pixels are usually a problem only in low light conditions.
- pixel signal level is so high that defect pixels are not visible or they can be easily corrected.
- bright light it is also possible to use longer exposure time without causing images that are blurred due to handshake.
- the illumination is low enough the exposure time achieves its maximum (limited by the handshake) and it is not possible to increase it any more. Therefore the local saturation signal optimization is well suited for bright light conditions, whereas global saturation signal may suit better for low light conditions. This is taken into account in the embodiment comprising switching between locally and globally optimized saturation signals depending on the illumination conditions.
- At least some features of the present invention may be implemented in software, hardware, application logic or a combination of software, hardware and/or application logic.
- the software, application logic and/or hardware may reside on any suitable imaging apparatus, such as a camera, or a mobile phone or a portable computing device having imaging capabilities.
- a "computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a camera or other imaging apparatus, with one example of an imaging apparatus described and depicted in Figure 7 below.
- the computer-readable medium may be a digital data storage such as a data disc or diskette, optical storage, magnetic storage, holographic storage, phase-change storage (PCM) or opto-magnetic storage.
- the computer-readable medium may be formed into a device without other substantial functions than storing memory or it may be formed as part of a device with other functions, including but not limited to a memory of a computer, a chip set, and a sub assembly of an electronic device.
- Figure 4 shows a block diagram of an apparatus 40 according to an example embodiment.
- the apparatus may be for example a camera, a mobile phone, an electronic communication device, or a portable computing device having imaging capabilities.
- the apparatus 40 a physically tangible object and comprises a camera module 42, and at least one memory 46 configured to store computer program code (or software) 47.
- the apparatus 40 further comprises at least one processor 41 for controlling at least some part of the operation of the apparatus 40 using the computer program code 47.
- the camera module 42 comprises a camera lens 44 and an image sensor 43.
- the camera module 42 is configured to capture images using the lens 44 and the sensor 43.
- the sensor comprises a plurality of photodetectors, such as photogates, that are configured to convert the light to which they are exposed to into signals for image generation.
- the at least one processor 41 may be a master control unit (MCU). Alternatively, the at least one processor 41 may be a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array, a microcontroller or a combination of such elements.
- Figure 4 shows one processor 41 , but the apparatus 40 may comprise a plurality of processors 41 .
- the at least one memory 46 may be, for example, random access memory, flash memory, hard disk, hard disk array, optical storage, memory stick, memory card and/or magnetic memory.
- the apparatus 40 may comprise other elements, such as user interfaces, displays, as well as communication units, and other additional circuitry such as input/output (I/O) circuitry, memory chips, and the like. Additionally, the apparatus 40 may comprise a disposable or rechargeable battery (not shown) for powering the apparatus 40.
- a communication unit included in the apparatus may be for example a radio interface module, such as a WLAN, Bluetooth, GSM/GPRS, CDMA, WCDMA, or LTE radio module. Such communication unit may be integrated into the apparatus 40 or into an adapter, card or the like that may be inserted into a suitable slot or port of the apparatus 40.
- the communication unit may support one radio interface technology or a plurality of technologies and there may be one or more such communication units.
- Figure 5 shows a block diagram of an image sensor 50 according to an example embodiment. It is to be noted that this is just an example of a sensor in which embodiments of the invention may be employed and that also some other kind of a sensor may apply.
- the sensor 50 comprises pixel/sensitive area 51 which comprises light detecting elements, such as photogates, configured to capture the light rays that arrive at the sensor. Additionally the sensor 50 comprises an analog-to-digital converter 52, interface 53 to external components, and a control unit 54.
- the analog-to-digital converter 52 is configured to convert captured light signals into digital form.
- the interface 53 is configured to output captured image data, for example. The interface may be used for receiving instructions or control signals from external components, too.
- the control unit 54 is configured to control operation of the sensor and may be configured to provide functionality according to various embodiments of the invention. Additionally the control unit 54 may be configured to provide other functionality.
- words comprise, include and contain are each used as open-ended expressions with no intended exclusivity.
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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Studio Devices (AREA)
- Transforming Light Signals Into Electric Signals (AREA)
Abstract
Description
Claims
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE112010005422T DE112010005422T5 (en) | 2010-03-29 | 2010-03-29 | Image sensor optimization |
| CN201080065874.5A CN102823235B (en) | 2010-03-29 | 2010-03-29 | Imageing sensor optimizes |
| PCT/FI2010/050243 WO2011121165A1 (en) | 2010-03-29 | 2010-03-29 | Image sensor optimization |
| US13/637,900 US9398279B2 (en) | 2010-03-29 | 2010-03-29 | Image sensor optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/FI2010/050243 WO2011121165A1 (en) | 2010-03-29 | 2010-03-29 | Image sensor optimization |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2011121165A1 true WO2011121165A1 (en) | 2011-10-06 |
Family
ID=44711389
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/FI2010/050243 Ceased WO2011121165A1 (en) | 2010-03-29 | 2010-03-29 | Image sensor optimization |
Country Status (4)
| Country | Link |
|---|---|
| US (1) | US9398279B2 (en) |
| CN (1) | CN102823235B (en) |
| DE (1) | DE112010005422T5 (en) |
| WO (1) | WO2011121165A1 (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI516133B (en) * | 2012-01-18 | 2016-01-01 | 聯詠科技股份有限公司 | Image processing device and method |
| CN106780626B (en) * | 2016-12-21 | 2019-03-05 | 维沃移动通信有限公司 | Method for adjusting camera parameters and mobile terminal |
| CN106998466B (en) * | 2017-03-31 | 2018-07-03 | 中国科学院新疆理化技术研究所 | CMOS active pixel sensor expires the test method of trap after irradiation |
Citations (5)
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| US6642496B1 (en) * | 2002-01-18 | 2003-11-04 | Raytheon Company | Two dimensional optical shading gain compensation for imaging sensors |
| US20040125226A1 (en) * | 2002-08-06 | 2004-07-01 | Naoki Kubo | Apparatus for compensating for shading on a picture picked up by a solid-state image sensor over a broad dynamic range |
| US20050030383A1 (en) * | 1999-06-30 | 2005-02-10 | Logitech Europe, S.A. | Image sensor based vignetting correction |
| US20070252073A1 (en) * | 2005-08-04 | 2007-11-01 | Korea Advanced Institute Of Science And Technology | High sensitivity and high dynamic-range CMOS image sensor pixel structure with dynamic C-V characteristics |
| US20090021632A1 (en) * | 2007-07-16 | 2009-01-22 | Micron Technology, Inc. | Lens correction logic for image sensors |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2687265A1 (en) | 1993-01-08 | 1993-08-13 | Scanera Sc | Electronic image acquisition device with very high dynamic range, and method of acquiring images of very highly contrasted scenes |
| US7327393B2 (en) * | 2002-10-29 | 2008-02-05 | Micron Technology, Inc. | CMOS image sensor with variable conversion gain |
| EP1447977A1 (en) | 2003-02-12 | 2004-08-18 | Dialog Semiconductor GmbH | Vignetting compensation |
| JP3731584B2 (en) * | 2003-03-31 | 2006-01-05 | コニカミノルタフォトイメージング株式会社 | Imaging apparatus and program |
| EP1564681A1 (en) | 2004-02-13 | 2005-08-17 | Dialog Semiconductor GmbH | Vignetting compensation algorithm |
| US7518645B2 (en) * | 2005-01-06 | 2009-04-14 | Goodrich Corp. | CMOS active pixel sensor with improved dynamic range and method of operation |
| EP1881452A1 (en) | 2006-07-21 | 2008-01-23 | STMicroelectronics (Research & Development) Limited | Special effects in image sensors |
| KR100830587B1 (en) | 2007-01-10 | 2008-05-21 | 삼성전자주식회사 | Image sensor and image display method using the same |
| US7920171B2 (en) | 2007-05-18 | 2011-04-05 | Aptina Imaging Corporation | Methods and apparatuses for vignetting correction in image signals |
| JP5098831B2 (en) * | 2008-06-06 | 2012-12-12 | ソニー株式会社 | Solid-state imaging device and camera system |
| US20110043674A1 (en) * | 2009-08-21 | 2011-02-24 | Samsung Electronics Co., Ltd. | Photographing apparatus and method |
| US8514322B2 (en) * | 2010-06-16 | 2013-08-20 | Aptina Imaging Corporation | Systems and methods for adaptive control and dynamic range extension of image sensors |
-
2010
- 2010-03-29 WO PCT/FI2010/050243 patent/WO2011121165A1/en not_active Ceased
- 2010-03-29 CN CN201080065874.5A patent/CN102823235B/en not_active Expired - Fee Related
- 2010-03-29 DE DE112010005422T patent/DE112010005422T5/en not_active Withdrawn
- 2010-03-29 US US13/637,900 patent/US9398279B2/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050030383A1 (en) * | 1999-06-30 | 2005-02-10 | Logitech Europe, S.A. | Image sensor based vignetting correction |
| US6642496B1 (en) * | 2002-01-18 | 2003-11-04 | Raytheon Company | Two dimensional optical shading gain compensation for imaging sensors |
| US20040125226A1 (en) * | 2002-08-06 | 2004-07-01 | Naoki Kubo | Apparatus for compensating for shading on a picture picked up by a solid-state image sensor over a broad dynamic range |
| US20070252073A1 (en) * | 2005-08-04 | 2007-11-01 | Korea Advanced Institute Of Science And Technology | High sensitivity and high dynamic-range CMOS image sensor pixel structure with dynamic C-V characteristics |
| US20090021632A1 (en) * | 2007-07-16 | 2009-01-22 | Micron Technology, Inc. | Lens correction logic for image sensors |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102823235B (en) | 2016-09-28 |
| DE112010005422T5 (en) | 2013-01-17 |
| CN102823235A (en) | 2012-12-12 |
| US9398279B2 (en) | 2016-07-19 |
| US20130070130A1 (en) | 2013-03-21 |
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