An image gradient is a directional change in the intensity or color in an image. The gradient of the image is one of the fundamental building blocks in...

Gradient domain image processing, also called Poisson image editing, is a type of digital image processing that operates directly on the differences between...

gradient of the image intensity function. At each point in the image, the result of the Sobel–Feldman operator is either the corresponding gradient vector...

the gradient direction. The zero-crossing based methods search for zero crossings in a second-order derivative expression computed from the image in order...

maps (transforms) the colors of one image to the colors of another image Diffusion curve dithering Image gradient Mach banding Ombré Palette; a finite...

Gradient echo is a magnetic resonance imaging (MRI) sequence that has wide variety of applications, from magnetic resonance angiography to perfusion MRI...

separated objects. Relief of the gradient magnitude Gradient magnitude image Watershed of the gradient Watershed of the gradient (relief) In geology, a watershed...

additional magnetic fields (gradients) that vary linearly over space, specific slices to be imaged can be selected, and an image is obtained by taking the...

rate. Gradient may also refer to: Gradient sro, a Czech aircraft manufacturer Image gradient, a gradual change or blending of color Color gradient, a range...

the gradient of the image intensity function. At each point in the image, the result of the Prewitt operator is either the corresponding gradient vector...

Pressure gradient Temperature gradient Geothermal gradient Sound speed gradient Wind gradient Lapse rate Grade (slope) Image gradient Time derivative Material...

The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The...

magnetic resonance imaging (MRI) is a particular setting of pulse sequences and pulsed field gradients, resulting in a particular image appearance. A multiparametric...

phase of zero by refocusing all imaging gradients. If, within one TR, either one of the gradient moments of magnetic gradients along three logical directions...

Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals instead of residuals as...

MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to form images of the organs in the body. MRI does not involve X-rays...

Gaussian filter to smooth the image in order to remove the noise Find the intensity gradients of the image Apply gradient magnitude thresholding or lower...

and digital image processing, a morphological gradient is the difference between the dilation and the erosion of a given image. It is an image where each...

PCA-SIFT descriptor is a vector of image gradients in x and y direction computed within the support region. The gradient region is sampled at 39×39 locations...

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate...

properties of the brain. Traditionally, in diffusion-weighted imaging (DWI), three gradient-directions are applied, sufficient to estimate the trace of...

2014. Xiangyu Y. Hu (2016). "Simple gradient-based error-diffusion method" (abstract). Journal of Electronic Imaging. 25 (4): 043029. Bibcode:2016JEI.....

that this method tends to uniformly penalize the image gradient irrespective of the underlying image structures. This causes over-smoothing of edges,...

spurious detail have high total variation, that is, the integral of the image gradient magnitude is high. According to this principle, reducing the total variation...

SWI uses a fully flow compensated, long echo, gradient recalled echo (GRE) pulse sequence to acquire images. This method exploits the susceptibility differences...

In machine learning, the vanishing gradient problem is the problem of greatly diverging gradient magnitudes between earlier and later layers encountered...

Perlin noise is a type of gradient noise developed by Ken Perlin in 1983. It has many uses, including but not limited to: procedurally generating terrain...

timed sequence of radiofrequency and gradient pulses. In practice, k-space often refers to the temporary image space, usually a matrix, in which data...

causes a gradient in the refractive index of the air. This produces a blurred shimmering effect, which hinders the ability to resolve the image and increases...

planes must be smaller than the pattern width. The fine-tuned gradient requires a pattern image more complex than standard repeating-pattern wallpaper, so...