Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
  • H04N1/40—Picture signal circuits
  • H04N1/407—Control or modification of tonal gradation or of extreme levels, e.g. background level
  • H04N1/4072—Control or modification of tonal gradation or of extreme levels, e.g. background level dependent on the contents of the original
  • H04N1/4074—Control or modification of tonal gradation or of extreme levels, e.g. background level dependent on the contents of the original using histograms
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N5/00—Details of television systems
  • H04N5/44—Receiver circuitry for the reception of television signals according to analogue transmission standards
  • H04N5/57—Control of contrast or brightness
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/10—Image enhancement or restoration using non-spatial domain filtering
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/40—Image enhancement or restoration using histogram techniques
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/90—Dynamic range modification of images or parts thereof
  • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/20—Special algorithmic details
  • G06T2207/20048—Transform domain processing
  • G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]

Definitions

• FIG. 1 is a block diagram of an exemplary general computing device for processing images
• FIG. 2 is an exemplary flow diagram of a computational model for contrast enhancement of an image
• FIGS. 3A and 3B illustrate an exemplary original image and an exemplary contrast enhanced image
• FIG 4A illustrates an exemplary nonlinear mapping function to enhance the image of FIG. 3 A to generate the image of FIG. 3b;
• FIG. 4B illustrates a histogram of the image in FIG. 3A.
• FIG. 4C illustrates a histogram of the contrast enhance image of FIG. 3B.
• contrast enhancement may be accomplished using an algorithm based on histogram modeling and spreading. "Spreading” is based on the physics of sound or heat propagation and may be used to determined parameters that do not need threshold tuning to perform the enhancement.
• FIG. 1 depicts an example operational environment that may be used to practice aspects of the present disclosure.
• FIG. 1 is a block diagram of an exemplary general computing device 100 for processing images.
• the device 100 may include a transform component 115, a histogram computation component 120, an estimation component 130, a processor component 135, and a communications component 140.
• the processor 135 provides the computing platform to perform the processes of the other components.
• the transform component 115 transforms histogram from one domain to another domain, such as the frequency domain in the case of DCT (discrete cosine transform) or FFT (fast Fourier Transform) of spatial data
• the transform component 115 may also perform inverse transformation such as the IDCT (inverse discrete cosine transform) or IFFT (inverse fast Fourier Transform).
• IDCT discrete cosine transform
• IFFT inverse fast Fourier Transform
• the histogram computation component 120 determines a histogram of an image.
• the histogram of an image is a graph showing the number of pixels in an image at each different intensity value found in that image. For an 8 -bit grayscale image, there are 256 different possible intensities; therefore, its histogram will graphically display 256 numbers showing the distribution of pixels amongst those grayscale values. Histograms can also be taken of color images as either individual histograms of red, green and blue channels or luminance and chrominance channels of other 3-D color space, where each histogram represents the pixel count distribution of each channel.
• the estimation component 130 may determine estimated parameters of a spreaded histogram model.
• the spreading is representative of properties of a physical process and is used to remap the intensity levels in the histogram over substantially of the available dynamic range.
• the estimation component 130 may also estimate parameters of Eigen functions of partial differential equations that are exponentially decaying sinusoids used to model the physical process.
• the communications component 140 contains logic used to receive data to be encoded from an external source 145.
• the external source 145 could be, for example, external memory, the Internet, a live video and/or audio feed, and receiving the data can include wired and/or wireless communications.
• the communications component 140 also contains logic to transmit (Tx) encoded data over a network 150.
• the network 150 can be part of a wired system such as telephone, cable, and fiber optic, or a wireless system.
• network 140 can comprise, for example, part of a code division multiple access (CDMA or CDMA2000) communication system or alternately, the system can be a frequency division multiple access (FDMA) system, a time division multiple access (TDMA) system such as GSM/GPRS (General Packet Radio Service)/EDGE (enhanced data GSM environment) or TETRA (Terrestrial Trunked Radio) mobile telephone technology for the service industry, a wideband code division multiple access (WCDMA), a high data rate (IxEV- DO or IxEV-DO Gold Multicast) system, or in general any wireless communication system employing a combination of techniques.
• CDMA code division multiple access
• TDMA time division multiple access
• WCDMA wideband code division multiple access
• IxEV- DO or IxEV-DO Gold Multicast high data rate
• the device 100 may have connected thereto, or integrally include, an audio device 112 (e.g., earpiece, headset), and an input device 116 (e.g., keypad, keyboard, stylus).
• An external storage 145 may be, for example, external RAM or ROM, or a remote server. Image data may be presented on a display component 160, stored in the external storage 145 or stored in internal memory of processor component 135.
• the display component 160 may be an integrated part of the device that contains such parts as video display hardware and logic, including a display screen or it can be an external peripheral device.
• the communications component 140 may also contain logic used to communicate the image data to the external storage component 145 or the display component 160.
• contrast enhancement is a remedy to overcome the ill-exposed (e.g., over or underexposed) images.
• Ill- exposed images tend to have pixels concentrated on a few, limited regions of available dynamic range. As a result, the image looks either too dark or too bright with few visible details.
• the histogram of such images is characterized by a few sharp peaks with sparsely occupied regions in between.
• the algorithm may follow principles of physics of sound or heat propagation to provide a contrast enhancement technique that is automatic and needs little threshold tuning or human interaction.
• the algorithm may be real-time implementable, and the resulting enhanced image has a histogram that resembles the original histogram in terms of global characteristics.
• the enhanced image may have a histogram that occupies substantially all of the entire dynamic range of the display.
• the ill-exposed histogram is an initial heat profile or distribution of a conductor
• this heat distribution will spread in an orderly and physically constrained manner.
• the spreading may stop as soon as the heat reaches the full scale.
• This spreading process has the properties that it is a physical process, where no threshold tuning or human interference is needed, and the spreaded heat profile closely resembles the characteristics of the original profile because the spreading is a physically constrained process. Heat would naturally and gradually reach the full scale available to it.
• FIG. 2 is an exemplary flow diagram of a computational model 200 for contrast enhancement of an image.
• the histogram of the image is determined. For an 8-bit grayscale image a histogram may be determined that graphically displays 256 numbers showing the distribution of pixels amongst those grayscale values. Histograms can also be taken of color images as either individual histograms of red, green and blue channels or luminance and chrominance channels of other 3-D color space, where each histogram represents the pixel count distribution of each channel.
• the nonlinear mapping for contrast enhancement is constructed.
• nonlinear mapping functions may be use where the dynamic range of a processed image exceeds the capability of a display device. In such cases, only the brightest parts of the image are visible on the display screen.
• Nonlinear mapping may be used to compress the dynamic range of pixel values, using e.g., a logarithmic intensity mapping (transformation) function such that the complete image will be visible on the display.
• FIG 4A illustrates an exemplary nonlinear mapping function.
• FIG. 4B illustrates a histogram of the image in FIG. 3A
• FIG. 4C illustrates a contrast enhance version of the histogram of FIG. 4B.
• the nonlinear mapping function in FIG. 4 A may be applied to the original histogram of FIG. 4B at 210 in FIG. 2 to produce the contrast enhanced histogram shown in FIG. 4C and the contrast enhanced image shown in FIG. 3B.
• the histograms of FIGS. 4B and 4C share substantially the same global characteristics, and the histogram of FIG. 4C occupies substantially all of the available dynamic range.
• FIG. 1 With regard to the a device 100 in FIG. 1, numerous other general purpose or special purpose computing system environments or configurations may be used. Examples of well known computing systems, environments, and/or configurations that may be suitable for use include, but are not limited to, PCs, server computers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, network PCs, minicomputers, mainframe computers, embedded systems, distributed computing environments that include any of the above systems or devices, and the like.
• Computer-executable instructions such as program modules, being executed by a computer may be used.
• program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types.
• Distributed computing environments may be used where tasks are performed by remote processing devices that are linked through a communications network or other data transmission medium.
• program modules and other data may be located in both local and remote computer storage media including memory storage devices.
• One or more programs may implement or utilize the processes described in connection with the presently disclosed subject matter, e.g., using an application programming interface (API), reusable controls, or the like.
• API application programming interface
• Such programs may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system.
• the program(s) may be implemented in assembly or machine language, if desired.
• the language may be a compiled or interpreted language and it may be combined with hardware imp lementations .
• exemplary implementations may refer to utilizing aspects of the presently disclosed subject matter in the context of one or more stand-alone computer systems, the subject matter is not so limited, but rather may be implemented in connection with any computing environment, such as a network or distributed computing environment. Still further, aspects of the presently disclosed subject matter may be implemented in or across a plurality of processing chips or devices, and storage may similarly be effected across a plurality of devices. Such devices might include personal computers, network servers, and handheld devices, for example.

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Theoretical Computer Science (AREA)
• Multimedia (AREA)
• Signal Processing (AREA)
• Image Processing (AREA)
• Facsimile Image Signal Circuits (AREA)
• User Interface Of Digital Computer (AREA)

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Citations (2)

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• 2008
  • 2008-07-08 US US12/169,439 patent/US8457399B2/en not_active Expired - Fee Related
• 2009
  • 2009-01-16 WO PCT/US2009/031304 patent/WO2009092018A1/en not_active Ceased
  • 2009-01-16 CN CN2009801013044A patent/CN101897173B/zh not_active Expired - Fee Related
  • 2009-01-16 KR KR1020127011702A patent/KR101239246B1/ko not_active Expired - Fee Related
  • 2009-01-16 EP EP09701591A patent/EP2229768A1/en not_active Ceased
  • 2009-01-16 KR KR1020107017658A patent/KR101205273B1/ko not_active Expired - Fee Related
  • 2009-01-16 JP JP2010543284A patent/JP5102370B2/ja not_active Expired - Fee Related
  • 2009-01-17 TW TW098101825A patent/TW201002045A/zh unknown

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