Improved spatial, temporal, and spatio-temporal noise reduction apparatus (10) and also apparatus for noise reduction in conjunction with one or several of the following functions: edge enhancement, spatial interpolation, magnification adjustment by spatial interpolation, and dynamic range compression (DRC). An embodiment of apparatus (10) comprises an image preprocessing unit (12), an estimation gain parameter computation unit (14) and a two-directional processor (16).

Apparatus and method for smoothing images

A method and apparatus for locating geometric shapes or edges thereof in data collection symbols initially samples and stores an image of light reflected from the symbol. Thereafter, two routines are performed. A first routine performs low level vision processing by identifying linked points along edges, lines, curves or within shapes. A rapid pixel linking subroutine identifies edge pixels in symbol images lacking distortion. If the edge or shape suffers from distortions, then one or more distortion compensating subroutines locate sequential linked pixels despite such distortions. The resulting coordinates of linked points, which represent lines, curves and other geometric shapes, are then employed by a second routine which identifies patterns within the identified lines/curves. Based on these identified patterns, types of symbols from various symbologies can be identified and located within the stored image.

Method and apparatus for automatic discriminating and locating patterns such as finder patterns, or portions thereof, in machine-readable symbols

A method and apparatus for locating geometric shapes or edges thereof in data collection symbols initially samples and stores an image of light reflected from the symbol. Thereafter, two routines are performed. A first routine performs low level vision processing by identifying linked points along edges, lines, curves or within shapes. At least one of three distortion compensating subroutines compensate for blocking, breaking, gaps or other severe distortions affecting shapes in the stored image. Under a first subroutine, an edge of a shape is tracked until a stopping condition occurs, at which point the shape is crossed so as to continue tracking on an opposite edge. Under a second subroutine, previously collected linear curve information is used to identify a jump point to continue tracking following a stopping condition. Under a third subroutine, mathematical morphology techniques are employed to close gaps or move blockage in shapes in the stored image. Coordinates of linked points, which represent lines, curves and other geometric shapes, from the first routine are then employed by a second routine which identifies patterns within the identified lines/curves. Based on these identified patterns, types of symbols from various symbologies can be identified and located within the stored image.

Non-linear image processing and automatic discriminating method and apparatus for images such as images of machine-readable symbols

A system is disclosed having a camera, a processor, and a user interface. The camera transmits image data responsive to a scene within a field of view. In response to the image data, the processor indicates whether a condition has been satisfied. The user interface is operably connected to the processor and allows a user to select criteria for detection of objects, for indicating criteria selected, and for providing visual confirmation that an object has been detected.

Sensor and imaging system

An apparatus and a method is provided for enhancing a digital image comprised of pixels by adaptively sharpening the pixels and clipping the numerical values of the sharpened edge pixels so as to fall between the smallest unsharpened numerical value and the greatest unsharpened numerical value, respectively, of the pixels located within a neighborhood of the pixels. Pixels which are located on an edge are sharpened in the direction perpendicular to the edge. The threshold value used to ascertain the presence of an edge and sharpening parameter used to control the degree of sharpening can be adaptively controlled by the zoom ratio. The apparatus of the invention is particularly suited for an electronic set-top video camera.

Electronic pan tilt zoom video camera with adaptive edge sharpening filter

Edge definition in FLIR images is improved by assigning to each pixel (X) the average intensity value of that 3×3 pixel sub-matrix (30a-30i) containing the pixel (X) which exhibits the smallest edge value. Apparatus for obtaining that intensity value in real time is disclosed. This process can be iteratively repeated on the same image, with each iteration creating more enhanced edges and greater area smoothing between edges.

Charles F. Raasch

Papers

Edge enhancement and smoothing in digital images