602 results about "Edge enhancement" patented technology

A binarization method for gray address images which combines high quality and high speed. The method is designed specifically for efficient software implementation. Two binarization approaches, localized background thresholds and Laplacian edge enhancement, are combined into a process to enhance the strengths of the two methods and eliminate their weaknesses. The image is divided into tiles, making binarization decisions for each tile. Tile decisions are modified based on adjacent tile decisions and then the tiles are binarized. Binarization of pixels is performed by performing background thresholding and edge detection thresholding. Only pixels exceeding both thresholds are selected as "on".

A focus state display apparatus comprising focus area extraction means for extracting the image signals of a predetermined area from photographed image signals, edge enhancement processing means for enhancing the edge of the extracted image signals, time integration value calculation means for calculating an integration value of the edge-enhanced image signals in a certain period of time, focus state determination means for determining the focus state of the photographed image signals on the basis of the calculated integration value, and focus state display means for displaying the determined focus state. A user is capable of readily determining the focus state of a camera and confirming and adjusting the focus thereof with accuracy even in a display apparatus of a camera-equipped portable terminal device, where the size and resolution thereof are limited.

A ceramic composite tile armor which is reinforced at the more vulnerable joint and free edge areas, using glass or ceramic strips or overlays bonded with an adhesive to the outer surface of the tile joints and free edges. This reinforcement provides improved ballistic threat protection for ground vehicle, aircraft, watercraft, spacecraft, and body (personnel) ceramic tile armor applications. Glass or ceramic overlay strips assist in fracturing impacting projectiles that strike the tile joints or free edges. The substrate laminate backing can then capture fragments of the projectile and broken ceramic and prevent penetration. The invention provides improved protection over conventional joint and edge enhancements with higher reliability of accurate positioning over joint and free-edge areas, with less added weight, and at lower associated production costs.

An image processing method for executing edge enhancement for an original image includes: extracting edge components based upon the original image; correcting the extracted edge components by attenuating the individual edge components so that a frequency distribution related to intensity of the edge components approximates a Gaussian distribution assuming a specific width; and executing edge enhancement for the original image based upon the corrected edge components.

Methods and apparatus for digital data array edge enhancement are disclosed. A local data window containing a data sample s is selected. Minimum and maximum sample values, max and min, are located within the window, and an edge deflection value ed is defined to have a value between max and min. A diffusion quantity is then calculated to move the value of s towards max, if s is greater than ed, or towards min, if s is smaller than ed. This approach has advantages over gradient-based edge-enhancement, including simplicity, convergence speed, and stability.

A filter assembly adapted to be used with a camera for selectively controlling the light that reaches the camera's aperture. In one embodiment, the filter assembly comprises three filters adapted to be independently moved between a first position wherein they are not in front of the camera's aperture and a second position wherein they are in front of the camera's aperture. The first and second filters are polarizing filters adapted to block portions of visible light. The third filter is an infrared filter adapted to block infrared light. In addition to moving between its first position and its second position, the second filter is also adapted to rotate up to 360 degrees. The image captured by the camera may be improved using a computer implemented image enhancement system that uses one or more of multi-spectral imaging, deconvolution, edge enhancement, and dynamic range translation.

A video signal processor includes an edge enhancement determining circuit that senses the amount of some characteristic of that signal which provides a measure of noise inherent in the signal, precisely determines a preferred amount of edge enhancement to be applied to a video signal as a function of that characteristic, and applies that amount of edge enhancement to the video signal. The video signal characteristic, used to determine the noise content of the video signal includes the amount of automatic gain control amplification and the brightness of the viewed scene. Thus, the amount of edge enhancement added to the video signal is adaptively controlled according to the brightness level of the viewed scene and the amplification level of the video signal by the automatic gain control circuit, and provides the proper amount of edge sharpness to the viewed video scene as a function of its noise content. This provides an increase in perceived sharpness of the viewed image, without an increase in background noise that occurs in conventional non-adaptive systems.

A method and apparatus for processing gray level image data. Gray level image data is subjected to plural separate halftone screen processing to form plural separate halftone processed screen gray level image data. The current pixel is also analyzed for contrast index. In response to analysis of the contrast index blending coefficients for processing of the halftone screen modified image data is made. The respective halftone outputs of the screen processings are multiplied by the respective blending coefficient. The resulting blended halftone gray value of the current pixel as well as neighboring pixels are then subjected to a threshold criterion test to determine if this represents a substantially binary image file such as might occur in a saturated text image file. The blended halftone gray value data for the current pixel is subjected to gray level edge enhancement processing to replace certain binary pixels adjacent an edge to reduce anti-aliasing effects. A signal resulting from the threshold criterion test is used to determine whether there is output to the printer or display of an edge enhanced version of the current blended halftone pixel or a pixel value representing the blended halftone pixel.

An apparatus for and method of processing a digital image are provided. The apparatus for processing a digital image includes: a detection unit which detects the direction or a magnitude of an edge of an input image signal; and an edge enhancement unit which determines the degree of enhancing the edge based on the detected direction or the detected magnitude of the edge, and enhances the edge of the input image signal according to the determined degree of enhancement.

A filter for post-processing digital images and videos, having an edge mapper, a pixel sorter, and an adaptive filter that simultaneously performs de-ringing and edge sharpening. The combined filter is computationally simpler than known methods and can achieve removal of ringing artifacts and sharpening of true edges at the same time. The present invention also includes a preferred method of simultaneously de-ringing and edge sharpening digital images and videos.

An edge enhancement processing system and method for modifying image data at certain pixel locations to include gray scale image data so as to reduce jaggedness in the image. An adjustable threshold device establishes a binary pixel value for an incoming current gray level pixel in accordance with a thresholding criterion. An operator accessible input to the thresholding device is used by the operator to adjust the threshold value in the thresholding criterion. A current binary pixel formed in accordance with the thresholding criterion and neighboring pixels also so formed in accordance with the thresholding criterion are examined in accordance with predetermined criteria for determining adjustment of the current pixel to a gray scale value to reduce edge jaggedness of the image. Generally, adjustment of the thresholding value is made in instances where under color removal and / or gray component replacement is employed.

A method for detecting and enhancing edges in an ultrasound image includes the steps of applying an edge detection filter to at least one of a plurality of pixels of an ultrasound image to compute an edge detection value having a magnitude and a direction; and applying either a directional edge enhancement filter or a non-directional smoothing filter to at least one of the plurality of pixels of the ultrasound image.

An edge enhancement system, including a selective edge controller for determining one or more properties of an edge of image data, and for generating one or more weighting factors on the basis of properties of the edge; and a scaling module for scaling an edge enhancement signal by the weighting factors to control the degree of edge enhancement. The image data may represent a still or moving (i.e., video) image. A max-min search circuit determines maximum and minimum turning points closest to the center of the data processing window and that are located on opposing sides of the window, to determine values and locations of maximum and minimum pixels of the edge. An edge-directed pre-filtering circuit reduces the amplification of edge fuzziness by smoothing close the edges vertical prior to enhancement. An aliasing protection circuit reduces the visibility of saw-tooth defects on predominantly horizontal diagonal edges.

The present invention is applied, for example, to resolution conversion. An edge gradient direction v1 with the largest gradient of pixel values and an edge direction v2 orthogonal to the edge gradient direction v1 are detected. Edge enhancement and smoothing processing are performed in the edge gradient direction v1 and in the edge direction v2, respectively, to generate output image data D2.

A system and method that enhance edges in images by detecting and correcting edges of the components of the image, such as the luma and the chroma components. The luma and the chroma edges may be corrected to align with one another. The luma edge detection may utilize a combination of the first and second derivatives of luma. The chroma edges may be sharpened by adjusting the saturation of the chroma components, without changing the hue. The luma edges may be corrected using a blend of peaking and enhancing the luma edges. The corrected chroma and luma components may be then debugged and the appropriate corrected components may be sent to display. Chroma / luma edge alignment may utilize a product of the luma first and second derivatives.

The invention relates to a self-adaptive low-illuminance or non-uniform-brightness image enhancement method. The method comprises the following steps: 1), preprocessing is performed on a low-illuminance and non-uniform-brightness image, wherein the preprocessing includes brightness preprocessing on the low-illuminance and non-uniform-brightness image, and edge enhancement is performed on the image after brightness preprocessing, so that the preprocessed image is obtained; 2), region segmentation is performed according to the brightness of the preprocessed image, corresponding mapping functions are selected according to the different characteristics of all segmented regions and corresponding self-adaptive brightness enhancement is performed; 3), saturation enhancement processing is performed on the image subjected to self-adaptive brightness enhancement segment by segment through the change characteristics of initial saturation and brightness. According to the invention, the steps are adopted to process the image, therefore, the color saturation of the image is improved, the image is enabled to be bright in color and have a better visual effect. The self-adaptive image enhancement method can be widely popularized in the fields of biomedicine, real-time monitoring, satellite remote sensing and the like.

A method and associated device wherein an inverse histogram based pixel mapping step is combined with an edge enhancement step such as unsharp masking. In such an arrangement the inverse histogram based pixel mapping step improves the performance of the unsharp masking step, serving to minimize the enhancement of noise components while desired signal components are sharpened.

Non-linear processing is performed in which noise reduction (smoothing) is serially performed for original data to reduce high-frequency noise components, the edge enhancement processing is performed for the smoothed image and, after that, noise components are reduced again. Finally, the created image is weighted-combined with the original image.

The invention discloses a stain detection method for a sensor of a digital camera, and a method and a device for classifying the sensor of the camera based on the detection method, wherein the method comprises the following steps: (1) inputting original image data and obtaining luminance component via interpolation, (2) low-pass filtering, (3) edge enhancement, (4) band-pass filtering, (5) image binaryzation operation and morphological dilation, (6) connectivity area abstraction, (7) marking stain in an original image, (8) classifying the sensor and outputting image level. The invention is divided as two function modules which are used for detecting the stain and classifying the sensor. A contiguous item of a classification decision function is from features such as quantity, area, and color depth of the stain detected in a shooting image. The method and the device of the invention is simple and efficient and can be used for fast detecting stain position on the sensor and carrying out accurate level evaluation to current sensor according to the feature of theses stains.

A method and system for digital cameras provides improved automatic exposure control, improved automatic white balance, improved color interpolation, improved automatic gamma correction, and improved progressive edge enhancement. These improvements are preferably implemented in CMOS semiconductor technology for faster speed.

Edge enhancement of a digital image can include using at least two signal processing paths to adjust a display-formatted pixel value to enhance the appearance of edges in displayed image data. A digital image can be filtered by producing an edge enhancement factor, a, per pixel from at least one look up table (LUT). Digital image data can also be adjusted using at least two signal processing paths, where the image data is adjusted if a pixel value and its neighboring pixel values are all within a smoothing range or where the pixel delta value is outside of a bad pixel range and its neighboring pixel delta values are all within the bad pixel range. In such cases, the image data can be adjusted by replacing the pixel value with an average or median value of the neighboring pixels.

In a signal-processing system, an image signal image captured by a CCD is converted into digital form by a preprocessing unit. An estimating unit estimates the amount of noise or a scene from the image signal as a characteristic amount. An edge-extracting unit extracts an edge component in an image associated with the image signal. A correction-coefficient calculating unit calculates a correction coefficient for correcting the edge component in accordance with the characteristic amount and the edge component. An edge-enhancing unit performs edge enhancement with respect to the image signal on the basis of the edge component and the correction coefficient.

A gradient-based image enhancement and restoration method and system which applies an orientation-isotropy adaptive filter to the gradients of high structured regions, and directly suppresses the gradients in the noise or texture regions. A new gradient field is obtained from which image reconstruction can progress using least mean squares. The method generally comprises: inputting image data; calculating image gradients; defining the gradients as having large or small coherence; filtering the large coherence gradients for edge enhancement; suppressing the small coherence gradients for noise reduction; assembling an enhanced gradient field from the filtered large coherence and suppressed small coherence gradients; and optimizing the assembled gradient field into a restored image.

The resolution of a low-resolution image is made high and a stereoscopic image is displayed. Resolution is made high by super-resolution processing. In this case, the super-resolution processing is performed after edge enhancement processing is performed. Accordingly, a stereoscopic image with high resolution and high quality can be displayed. Alternatively, after image analysis processing is performed, edge enhancement processing and super-resolution processing are concurrently performed. Accordingly, processing time can be shortened.