lec11 - SUV Color Space and Filtering Computer Vision I...

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
1 CS252A, Fall 2010 Computer Vision I SUV Color Space and Filtering Computer Vision I CSE252A Lecture 11 ,© David Kriegman ,© David Kriegman Diffuse Surface ,© David Kriegman Transparent Film ,© David Kriegman Dielectric Surface ,© David Kriegman +
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
2 ,© David Kriegman ,© David Kriegman Data-dependent. Rotational (hence, linear) Transformation. The S channel encodes the entire specular component and an unknown amount of diffuse component. Shading information is preserved. ,© David Kriegman S U V RGB ,© David Kriegman ,© David Kriegman ,© David Kriegman
Background image of page 2
3 ,© David Kriegman CS252A, Fall 2010 Computer Vision I Image Filtering CS252A, Fall 2010 Computer Vision I (From Bill Freeman) CS252A, Fall 2010 Computer Vision I Noise • Simplest noise model – independent stationary additive Gaussian noise – the noise value at each pixel is given by an independent draw from the same normal probability distribution Issues – this model allows noise values that could be greater than maximum camera output or less than zero – for small standard deviations, this isn’t too much of a problem - it’s a fairly good model – independence may not be justified (e.g. damage to lens) – may not be stationary (e.g. thermal gradients in the ccd) CS252A, Fall 2010 Computer Vision I Linear Filters General process: – Form new image whose pixels are a weighted sum of original pixel values, using the same set of weights at each point. Properties – Output is a linear function of the input – Output is a shift-invariant function of the input (i.e. shift the input image two pixels to the left, the output is shifted two pixels to the left)
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 12/08/2010 for the course CSE 252a taught by Professor Staff during the Fall '08 term at UCSD.

Page1 / 10

lec11 - SUV Color Space and Filtering Computer Vision I...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online