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2255 results about "Color space" patented technology

A color space is a specific organization of colors. In combination with physical device profiling, it allows for reproducible representations of color, in both analog and digital representations. A color space may be arbitrary, with particular colors assigned to a set of physical color swatches and corresponding assigned color names or numbers such as with the Pantone collection, or structured mathematically as with the NCS System, Adobe RGB and sRGB. A "color model" is an abstract mathematical model describing the way colors can be represented as tuples of numbers (e.g. triples in RGB or quadruples in CMYK); however, a color model with no associated mapping function to an absolute color space is a more or less arbitrary color system with no connection to any globally understood system of color interpretation. Adding a specific mapping function between a color model and a reference color space establishes within the reference color space a definite "footprint", known as a gamut, and for a given color model this defines a color space. For example, Adobe RGB and sRGB are two different absolute color spaces, both based on the RGB color model. When defining a color space, the usual reference standard is the CIELAB or CIEXYZ color spaces, which were specifically designed to encompass all colors the average human can see.

Dynamic contrast enhancement device and method

The invention relates to a dynamic contrast enhancement device and a dynamic contrast enhancement method. The device comprises a color space switching module, a histogram statistical module, an enhanced mapping function module and a brightness transformation module, wherein the color space switching module is used for switching an input image data from a red, green and blue (RGB) color space to aluma and chroma (YUV) color space; the histogram statistical module is used for counting a gray histogram of an image according to a brightness component Y; the enhanced mapping function module is used for calculating weights of a plurality of brightness component intervals in the histogram and obtaining an adaptive mapping function f according to the designed mapping table of each brightness component interval and the weights; and the brightness transformation module is used for transforming the brightness Y of the image to a novel brightness Y' according to the adaptive mapping function f, and outputting the brightness in the RGB color space through the color space switching module. By the device, the image is divided into the plurality of brightness component intervals, the weights arecalculated respectively, and the adaptive mapping function is obtained by a weighting method to transform the image brightness; therefore, the processed image can keep a mean brightness, the contrastis effectively improved, and the problems of level reduction and details loss caused by the traditional histogram equalization are solved.
Owner:王洪剑

Method and apparatus for automated image analysis of biological specimens

A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space. The color space converted image is then low pass filtered and compared to a threshold to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed to group candidate object of interest pixels together into groups which are compared to blob parameters to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification. The high magnification images are analyzed in the same manner as the low magnification images to confirm the candidate objects of interest which are objects of interest. A high magnification image of each confirmed object of interest is stored for later review and evaluation by a pathologist.
Owner:CARL ZEISS MICROSCOPY GMBH
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