6 results about "Value noise" patented technology

Apparatuses, systems, and techniques to generate blue noise masks for real-time image rendering and enhancement. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more enhanced images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes vector values per pixel and is able to handle the temporal domain (e.g., add time to the spatial domain) to improve image quality when rendering images over multiple frames.

The present disclosure relates to spatio-temporal noise masks and sampling using vectors for image processing and light transport simulation systems and applications, and in particular to apparatuses, systems, and techniques for generating blue noise masks for real-time image rendering and augmentation. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more augmented images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes a vector value per pixel and is capable of handling the temporal domain (e.g., adding time to the spatial domain) to improve image quality when rendering images over multiple frames.

A system and method of analog to digital conversion including an adjustable ADC, FIR filter circuitry, and a noise setting controller. The ADC samples an analog input signal to provide digital samples at a sample rate that is Y times an output rate of output digital values. The FIR filter circuitry includes Y taps with Y corresponding coefficients and is configured to filter the digital samples from the ADC and to provide filtered digital samples at the sample rate. decimation circuitry may be included to decimate the filtered digital samples by Y to provide the output digital values. The noise setting controller provides an adjustment value to the ADC to adjust noise contribution of the digital samples provided by the ADC based on corresponding coefficients of the FIR filter circuitry. The ADC is adjusted to reduce noise contribution of digital samples that correspond with higher FIR filter coefficients.

The invention provides a signal noise reduction method and a gas concentration detection method based on an improved threshold function. The signal noise reduction method comprises the following steps: decomposing an original signal containing noise into a plurality of signal components; wavelet threshold noise reduction processing is carried out on at least part of the signal components, and wavelet coefficients are processed through an improved threshold function in the processing process; and performing signal reconstruction based on a wavelet threshold noise reduction processing result to obtain a de-noised signal. A threshold function containing an exponential attenuation item is introduced, the function is continuous and smooth at a threshold point, when the amplitude of a wavelet coefficient is just larger than a threshold, the function can provide smooth shrinkage similar to a soft threshold, and signal oscillation caused by a hard threshold function is effectively avoided; when the amplitude of the wavelet coefficient is far greater than a threshold value, the exponential attenuation item rapidly approaches zero, so that the processed coefficient infinitely approaches the original coefficient; noise with small amplitude can be filtered out, high-fidelity preservation can be carried out on a large-amplitude coefficient, and the signal noise reduction precision and the waveform fidelity are remarkably improved.

The invention relates to a bristle number and integrity detection method based on pixel features and a self-adaptive threshold value, which comprises the following steps of: firstly, acquiring an initial image through the combination of bottom main backlight and side auxiliary backlight, then converting a color image into a grey-scale image, performing smoothing processing, positioning by adopting a morphological opening operation and eliminating reflective interference, and finally obtaining a bristle number and integrity detection result. The method comprises the following steps: performing four-direction edge detection fusion, brightening an image to four corners, calculating edge definition, outputting a qualified brightened image after optimization, performing block calculation on the image to calculate four-direction gradient and characteristic related parameters of each pixel, subtracting a mean noise map from the brightened image to obtain an illumination uniform correction image, determining a threshold value by adopting an between-class variance method, and outputting a final correction image. Bristles and background pixels are distinguished, connected domain detection statistics is carried out on the finally judged white pixels, and the number and integrity of the bristles are judged; the method effectively resists the detection of the white pixels of the bristles caused by the interference such as light reflection and uneven illumination, and can adaptively adjust the parameters to adapt to the detection of the bristles of different materials and specifications.

The present application relates to the technical field of image data processing, and more particularly to a kind of based on fractional order total variation GM-APD laser radar range image denoising algorithm.The algorithm includes the following steps: step S1, original data is estimated by maximum likelihood estimation algorithm pixel by pixel distance parameter, realize the extraction of GM-APD range image;Step S2, introduce fractional order differential operator to construct FOTV model, obtain the spatial relationship and similarity relationship between pixels using spatial kernel function and value domain kernel function to optimize fractional order differential operator, construct FOTVGM-APD laser radar denoising model based on spatial kernel function and value domain kernel function;Step S3, split Bregman algorithm is used for range image denoising.The present application realizes the suppression of GM-APD laser radar range image lost information and distance abnormal value noise, while retaining target details and contour information.