interpolation

can any one please help me in filling these black holes by values taken from neighboring non-zero pixels. thanks There is a file on Matlab file exchange, - inpaint_nans that does exactly what you want. The author explains why and in which cases it is better than Delaunay triangulation. One nice way to do this is to is to solve the linear heat equation . What you do is fix the "temperature" (intensity) of the pixels in the good area and let the heat flow into the bad pixels. A passable, but somewhat slow, was to do this is repeatedly average the image then set the good pixels back to their

I've been having some troubles making custom Interpolation, gone through every example I could find on web, but no matter what I did, had no success. At the moment I have this: Model has_attached_file :photo, :path => ":rails_root/public/images/:img_name-:style.:extension", :styles => { :original => '100x100', :thumb => '30x30' } initializers/paperclip.rb Paperclip.interpolates :img_name do |attachment, style| attachment.instance.img_name end img_name is field populated in form on upload with the image. The error I get on upload is: Invalid argument - (C:/Users/.../stream20110410-384

I'm trying to create an OpenGL ES 2.0 fragment shader that outputs multiple stop gradient along one axis. It should interpolate between multiple colors at points defined in percents. I've achieved this by using if s the fragment shader, like this: float y = gl_FragCoord.y; float step1 = resolution.y * 0.20; float step2 = resolution.y * 0.50; if (y < step1) { color = white; } else if (y < step2) { float x = smoothstep(step1, step2, y); color = mix(white, red, x); } else { float x = smoothstep(step2, resolution.y, y); color = mix(red, green, x); } They say that branching in fragment shader can

I have a trajectory formed by a sequence of (x,y) pairs. I would like to interpolate points on this trajectory using splines. How do I do this? Using scipy.interpolate.UnivariateSpline doesn't work because neither x nor y are monotonic. I could introduce a parametrization (e.g. length d along the trajectory), but then I have two dependent variables x(d) and y(d) . Example: import numpy as np import matplotlib.pyplot as plt import math error = 0.1 x0 = 1 y0 = 1 r0 = 0.5 alpha = np.linspace(0, 2*math.pi, 40, endpoint=False) r = r0 + error * np.random.random(len(alpha)) x = x0 + r * np.cos(alpha)

I need to have an image render with nearest-neighbor resizing and not the bicubic way that is currently used. I currently use the following: ms-interpolation-mode: nearest-neighbor; image-rendering: -moz-crisp-edges; This works in IE and Firefox, but not in Chrome and Safari. Are there any webkit alternatives or any other way to achieve this effect? thirtydot Edit: It's now possible with image-rendering: -webkit-optimize-contrast; . https://developer.mozilla.org/en-US/docs/CSS/image-rendering#Examples This doesn't work in current versions of Chrome, here are some useful links: http:/

I have a scatterplot in R. Each (x,y) point is colored according to its z value. So you can think of each point as (x,y,z) , where (x,y) determines its position and z determines its color along a color gradient. I would like to add two things A legend on the right side showing the color gradient and what z values correspond to what colors I would like to smooth all the color using some type of interpolation, I assume. In other words, the entire plotting region (or at least most of it) should become colored so that it looks like a huge heatmap instead of a scatterplot. So, in the example below,