121 results about "Temporal noise" patented technology

A method of reducing noise levels in an input video signal comprising pixel data includes receiving input pixel data of the input video signal, where the input pixel data comprises luminance data and chrominance data, and estimating a noise level of the input video signal using the luminance data of the input pixel data. A plurality of filter parameters are identified based on the estimated noise level, and the input pixel data is filtered using a three dimensional spatiotemporal noise reduction filter that is controlled by a first set of the plurality of filter parameters. Thereafter, the method includes filtering the filtered input pixel data using a one dimensional temporal noise reduction filter with motion compensation that is controlled by a second set of the plurality of filter parameters, and generating a noise-filtered output video signal that includes the filtered input pixel data from the three dimensional spatiotemporal noise reduction filter and the motion compensated filtered input pixel data from the one dimensional temporal noise reduction filter.

An improved temporal noise reduction method and system detects the global motion and adjusts the overall gain of the temporal filtering. Temporal noise reduction is applied to two video frames, wherein one video frame is the current input noisy frame, and the other video frame is a previous filtered frame stored in memory. In this method, noise estimation is first performed to estimate the noise variance/standard deviation in the input video sequence. Then, motion estimation is applied to obtain the motion vectors indicating relative motion between the pixels in the current noisy frame and the corresponding pixels in the previous noise-reduced frame. From such motion vectors, global motion estimation is applied to estimate the camera motion of the video sequence. If reliable global motion is obtained, the overall gain of the temporal filtering is reduced by adjusting the estimated noise level. Motion blur is thus prevented.

A motion-adaptive temporal noise reducing method and system for reducing noise in a sequence of video frames is provided. Temporal noise reduction is applied to two video frames, wherein one video frame is the current input noisy frame, and the other video frame is a previous filtered frame stored in memory. Once the current frame is filtered, it is saved into memory for filtering the next incoming frame. A motion-adaptive temporal filtering method is applied for noise reduction. Pixel-wise motion information between the current frame and the previous (filtered) frame in memory is examined. Then the pixels in the current frame are classified into motion region and non-motion region relative to the previous (filtered) frame. In a non-motion region, pixels in the current frame are filtered along the temporal axis. In a motion region, the temporal filter is switched off to avoid motion blurring.

A content-dependent scan rate converter with adaptive noise reduction that provides a highly integrated, implementation efficient de-interlacer. By identifying and using redundant information from the image (motion values and edge directions), this scan rate converter is able to perform the tasks of film-mode detection, motion-adaptive scan rate conversion, and content-dependent video noise reduction. Adaptive video noise reduction is incorporated in the process where temporal noise reduction is performed on the still parts of the image, thus preserving high detail spatial information, and data-adaptive spatial noise reduction is performed on the moving parts of the image. A low-pass filter is used in flat fields to smooth out Gaussian noise and a direction-dependent median filter is used in the presence of impulsive noise or an edge. Therefore, the selected spatial filter is optimized for the particular pixel that is being processed to maintain crisp edges.

A three-dimensional filter that addresses various types of noise is described. This filter uses both spatial and temporal characteristics of the video signal in the filtering process. Additionally, the filter is able to maintain edge fidelity within in images in the video signal.

An apparatus for removing a noise of a video signal is disclosed, by which a noise level can be effectively estimated to enhance an image quality of the video signal, by which the noise can be removed in a manner of effectively estimating a noise level though motion adaptive filtering, and by which blurring is prevented in the process of removing the noises. The present invention includes a temporal noise level estimation unit estimating a level of a temporal noise included in the video signal using a difference between two temporally consecutive videos, a noise correction unit correcting a noise estimated by the temporal noise level estimation unit, and a noise removal unit removing the noise included in the video signal using a level of the corrected noise.

A non-traditional, non-uniformity compensation processor. In the illustrative embodiment, the feedforward adaptive non-uniformity compensation processor includes a multiplier which receives a video image and generates a compensated video image by multiplying the video signal by one of a noise reducing constant or one. The inventive processor further includes a shunting multiplication processor which supplies a selected one of the noise reducing constant or one to the multiplier in response to the presence of one of fixed pattern noise (FPN) and temporal noise (TN) in adjacent frames of the video image. In an illustrative embodiment, the inventive system cones the output of an FPA to generate a coned output signal. The system isolates the FPN in the coned output signal and feedforward processes the coned output signal on a pixel-by-pixel basis to generate a FPN-reduced output signal. In an exemplary embodiment, the feedforward processing step includes the step of multiplying the coned output signal by a predetermined value which is substantially smaller, i.e., approximately zero, than the coned output signal.

An apparatus for decoding an encoded audio signal, includes: a spectral domain audio decoder for generating a first decoded representation of a first set of first spectral portions being spectral prediction residual values; a frequency regenerator for generating a reconstructed second spectral portion using a first spectral portion of the first set of first spectral portions, wherein the reconstructed second spectral portion additionally includes spectral prediction residual values; and an inverse prediction filter for performing an inverse prediction over frequency using the spectral residual values for the first set of first spectral portions and the reconstructed second spectral portion using prediction filter information included in the encoded audio signal.

A noise measurement apparatus and a method thereof capable of reducing an error in measuring a noise of incoming image signals. A picture of an incoming image signal is broken into at least two blocks and an average brightness value with respect to each block is calculated in a sequence. At least two first data, each being a sum of differences between the calculated average brightness value and brightness values of respective constituent pixels of the block, where the average brightness value is calculated, and a spatial noise is calculated based on the at least two first data. At least two second data that indicate a difference a brightness value of each block of the picture and a brightness value of each block of a delayed picture is calculated, and a temporal noise is calculated based on the at least two second data. A noise on the image signal is calculated based on the spatial noise and the temporal noise.

A system and method adapted for use with a focal plane array of electromagnetic energy detectors to receive first and second frames of image data from electromagnetic energy received from at least a portion of a scene. The first frame is a focused frame and the second frame is an unfocused frame. In a feed-forward path the system compares the first frame to the second frame and provides an error signal in response thereto. In a main path, the system multiplies at least a portion of the second frame of image data with the error signal to provide an noise error corrected output signal. In the preferred embodiment, the error signal is scaled prior to being multiplied by the second frame. An anti-mean (high pass) filter is provided to remove dome shading effects from the frames of image data. In the best mode, the anti-mean filter is disposed in the main path and blurred and focused outputs therefrom are weighted, averaged and stored. The weighted, averaged and stored focused frames are compared to the weighted, averaged and stored blurred frames to provide a fixed pattern noise error signal. A temporal noise error signal is identified from the weighted, averaged and stored focused frames. The fixed pattern and temporal noise error signals are fed forward and shunted from a current frame using multiplication or division. Thereafter, a constant mean value may be added to provide the output signal. Pixel replacement is consolidated into a single circuit and positioned prior to the anti-mean filter.

A method of reducing noise in a sequence of digital video frames is performed by motion estimation between a current noisy frame and a previous noise-reduced frame, to generate motion vectors indicating relative motion between the pixels in the current noisy frame and the corresponding pixels in the previous noise-reduced frame; and removing noise from the current noisy frame by computing the weighted average of pixels in the current noise frame and the corresponding pixels in the previous noise-reduced frame based on the motion vectors, to generate a noise-reduced output frame.

A dual sensitivity image sensor provides a standard mode and a high-sensitivity mode of operation via iSoC integration. In addition to boosting sensitivity, the high sensitivity mode also reduces temporal noise thereby optimally boosting the Signal-to-Noise Ratio (SNR) of the image sensor. The circuit does not significantly increase pixel complexity and requires minimal changes to the support circuits in the iSoC including the addition of support and control circuitry to facilitate seamless mode change.

An over sampled image sensor in which the pixel size is small enough to provide spatial oversampling of the minimum blur size of the sensor optics is disclosed. Image processing to detect targets below the typical limit of 6× the temporal noise floor is also disclosed. The apparatus is useful in detecting dimmer targets and targets at a longer range from the sensors. The inventions exploits signal processing, which allows spatial temporal filtering of the superpixel image in such manner that the Noise Equivalent Power is reduced by a means of Superpixel Filtering and Pooling, which increases the sensitivity far beyond a non-oversampled imager. Overall visual acuity is improved due to the ability to detect dimmer targets, provide better resolution of low intensity targets, and improvements in false alarm rejection.

A noise reduction system is provided. In a temporal module, a temporal characteristic detector detects a temporal characteristic of the input image based on the input image and a reference image. A temporal filter performs temporal noise reduction on the input image based on the reference image and the temporal characteristic to generate a temporal filtered image. A temporal selector selects the temporal filtered image or the input image as a preliminary output accordingly. In a spatial module, a spatial characteristic of the input image is detected. A spatial filter performs spatial noise reduction on the input image based on the preliminary output and the spatial characteristic to generate a spatial filtered image. A spatial selector selects the spatial filtered image or the preliminary output as the output image based on the temporal or spatial characteristics.

A spatio-temporal noise removal method using block classification that removes noise from a third field by using first, second, and third fields which are continuously inputted. The method includes generating first, second, and third motion-compensated fields; classifying blocks of the third field into a uniform region and a non-uniform region based on a variance value of a generated difference image; performing temporal filtering over every block of the third field; performing spatio-temporal filtering over every block of the first and third motion-compensated fields and the third field and performing the temporal filtering over the every block of the third field based on spatially-filtered value; and outputting a third noise-removed field by applying a weighted value to the temporal-filtered value and the spatio-temporal-filtered value.

An apparatus, method, mobile station and computer program product are provided for filtering noise from a digital signal. In particular, a signal-dependent noise model is used that provides the pointwise (or pixelwise) standard deviation of the temporal noise of raw data outputted from a digital imaging sensor as a function of the image intensity. In addition, unlike conventional noise models, the standard deviation of the noise (σ) is a parameterized function, where the parameters are key characteristics of the digital imaging sensor. These parameters may include, for example, the pedestal level (p), the quantum efficiency (q), and the analogue gain (α) associated with the digital imaging sensor.

Embodiments of the invention are directed to methods and apparatus for infrared imagers including fast electrostatic shutters and offset compensation. Fast electrostatic shutters are used for video image correction including image offset compensation where temporal noise and scene nonuniformity are corrected. This method provides a shutterless experience for the user because the image will be blocked for only one frame at a time. A method of manufacturing an electrostatic infrared shutter includes a conductive infrared-transparent substrate, covering it with an insulating layer, depositing adhesive and a thin film stack, delineating a working area, providing contacts, heat-treating the assembly, and making the polymer non-reflective in the infrared.

An image processing apparatus and a processing method thereof are provided. The image processing apparatus includes an image capturing module, an image separation module, an image stabilization module, a temporal noise reduction module, and a spatial noise reduction module. The image capturing module captures a plurality of Bayer pattern images. The image separation module decreases the Bayer pattern images in size and transforms them into a plurality of YCbCr format images. The image stabilization module receives Y channel images of the YCbCr format images and the Bayer pattern images to perform motion estimation, to produce a plurality of global motion vectors (GMVs). The temporal noise reduction module performs temporal blending process on the Bayer pattern images according to the GMVs, to produce first noise reduction images. The spatial noise reduction module performs 2-dimensional spatial noise reduction on the first noise reduction images to produce second noise reduction images.