Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T9/00—Image coding
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
  • H04N19/117—Filters, e.g. for pre-processing or post-processing
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
  • H04N19/136—Incoming video signal characteristics or properties
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
  • H04N19/182—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a pixel
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
  • H04N19/186—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a colour or a chrominance component
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
  • H04N19/98—Adaptive-dynamic-range coding [ADRC]
• • 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
  • H04N9/646—Circuits for processing colour signals for image enhancement, e.g. vertical detail restoration, cross-colour elimination, contour correction, chrominance trapping filters

Definitions

• the invention relates to a method for performing dynamic compression in traffic photography for more detailed representation in images that were created in connection with traffic surveillance systems.
• the object of the invention is to find a way to achieve a more detailed representation of the dark areas in digitally obtained images of traffic photography, excluding the different subjective influences from the editing staff, without losing the information of the brighter areas.
• this object is achieved by a method for carrying out a dynamic compression in traffic photography.
• the arithmetic mean value is calculated over all gray values G (Sii; z i2 ) according to
• a gain parameter p and a blur factor b are then determined.
• a blurred gray value image (contrast mask) [U] with the gray values Xu, by blurring with the Blur factor b is created to finally the desired new image [N] with the pixels x N i by superimposing the image original [F] with the pixels x F i with the blurred gray value image (contrast mask) [U] with the pixels Xu, with the inclusion of Gain parameter p and an exponent Vu.
• the particular advantage of the method according to the invention is that the dark areas are automatically lightened, particularly in the case of color images with high dynamics, in order to better visualize details that are initially not visible in these areas, but without destroying the information in the brighter areas.
• This method can be applied both in the camera immediately after the detection in such a way that all the image original are automatically lightened or after the image sources have been stored on a storage medium.
• the temporally downstream brightening can take place in the camera at a time in which no image original is detected, or on a separate arithmetic unit, for example on a computer in a back office.
• the starting point for the method can be both a monochrome gray value image [F] and a color image [F] with the usual 3 channels (RGB).
• the gray value image mask with its gray values x G i is thereby generated by converting the individual R, G and B pixels as follows:
• each pixel is then split again into an R, G and B pixel.
• Fig. 1 shows a schematic sequence of the method based on a color image
• floating point Since all computers today use so-called floating-point, floating-point, floating-point or floating-point arithmetic ("floating point"), at the beginning of the process all color values from fixed-point arithmetic (integer) to floating-point arithmetic, i. H. Floating point numbers converted to keep rounding errors in the calculation steps as low as possible.
• each R, G and B value for each pixel is divided by 65,536.0:
• Gray values x G i, where i 1, ..., n * m, created.
• the starting point for the method can be both a monochrome gray value image [F] and a color image [F] with the usual 3 channels (RGB).
• the color image [F] is first converted into a monochrome image.
• a copy of the image original [F] is first generated from the color image [F] and subsequently converted into a monochrome image [G].
• the gray value image [G] with its gray values x G i is generated by converting the individual R, G and B pixels as follows:
• a blurred gray scale image is generated for later use.
• the blur filter eg a Gaussian filter
• a two-dimensional filter H (x, y) can be separated into two one-dimensional filters H (x) and H (y).
• the original image [F] is compared pixel by pixel with the blurred gray value image [U] (contrast mask).
• the calculation takes place as a function of a gain parameter p determined once for all calculations of an image and of the pixel-dependent parameter x ui, which both flow into the exponent specific for each pixel.
• gain parameter p is first used with the aid of the arithmetic mean value
• v Ui 10l 50
• x ui are the values of the blurred gray value image (contrast mask)
• p is the gain parameter calculated using the arithmetic mean value x. The dark parts of the picture are amplified without changing the bright picture parts too much.
• FIGS. 1 and 2 the process sequences explained in greater detail above are illustrated schematically, wherein in FIG. 1 a color image and in FIG. 2 a monochromatic image are assumed.
• Gray value image (gray value mask) with gray values x G i

Landscapes

• Engineering & Computer Science (AREA)
• Multimedia (AREA)
• Signal Processing (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Theoretical Computer Science (AREA)
• Image Processing (AREA)
• Closed-Circuit Television Systems (AREA)

Applications Claiming Priority (2)

Publications (1)

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Family Applications (1)

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• 2011
  • 2011-11-11 DE DE102011055269A patent/DE102011055269A1/de not_active Withdrawn
• 2012
  • 2012-11-10 CN CN201280055188.9A patent/CN103931198B/zh active Active
  • 2012-11-10 DE DE112012004684.6T patent/DE112012004684A5/de not_active Withdrawn
  • 2012-11-10 US US14/357,709 patent/US9153038B2/en active Active
  • 2012-11-10 EP EP12794852.9A patent/EP2777271A2/de not_active Withdrawn
  • 2012-11-10 WO PCT/DE2012/100345 patent/WO2013068006A2/de active Application Filing

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