A Numerical Tour of Signal Processing: snr(x,y) - File Exchange

Code covered by the BSD License

Highlights from
A Numerical Tour of Signal Processing

[p,ellipse]=phantom(varargin) PHANTOM Generate a head phantom image.
b=dct(a,n) DCT Discrete cosine transform.
b=dct2(arg1,mrows,ncols) DCT2 Compute 2-D discrete cosine transform.
cat3(d, a,b) cat3 - synonymous with cat
cconv(x,h,d) cconv - spatial domain circular convolution
cell_add(A,B,a,b) cell_add - add two cell arrays
cell_get(x,i) cell_get - get value
cell_set(x,i,v) cell_set - assign value
cell_sub(x,sel) cell_sub - extract a sub-cell array
clamp(x,a,b)
compute_conditional_histogram... compute_conditional_histogram - compute conditional histograms
compute_entropy(M,T) compute_entropy - compute the entropy of a signal
compute_gaussian_filter(n,s,N... compute_gaussian_filter - compute a 1D or 2D Gaussian filter.
compute_histogram(M, options) compute_histogram - compute the (symmetric) histogram of a vector after threshold.
compute_hufftree(p) compute_hufftree - build a huffman tree
compute_l2err(MF, donormalize... compute_l2err - non linear approximation error
compute_max(X,d) compute_max - compute maximum along dimension d
compute_min(X,d) compute_min - compute min along dimension d
compute_quadsel(j,q, options) compute_quadsel - compute the indices for selecting subband of a wavelet transform.
compute_shape_boundary(M) compute_shape_boundary - extract boundary points of a shape
compute_total_variation(y, op... compute_total_variation - compute the total variation of an image
compute_wavelet_filter(Type,P... compute_wavelet_filter - Generate Orthonormal QMF Filter for Wavelet Transform
crop(M,n,c) crop - crop an image to reduce its size
det3(A) det3 - 3x3 determinant
div(Px,Py, options) div - divergence operator
extend_stack_size(mult) does nothing
gamrnd(a,b,m,n); GAMRND Random matrices from gamma distribution.
getoptions(options, name, v, ... getoptions - retrieve options parameter
grad(M, options) grad - gradient, forward differences
huffman_gencode(T) huffman_gencode - generate a code associated to a Hufmann tree T
idct(b,n) IDCT Inverse discrete cosine transform.
idct2(arg1,mrows,ncols) IDCT2 Compute 2-D inverse discrete cosine transform.
image_resize(M,p1,q1,r1) image_resize - resize an image using bicubic interpolation
imageplot(M,str, a,b,c) imageplot - diplay an image and a title
iradon(varargin) IRADON Compute inverse Radon transform.
load_image(type, n, options) load_image - load benchmark images.
load_signal(name, n, options) load_signal - load a 1D signal
load_sound(name, n0, options)
mad(x,flag) MAD Mean/median absolute deviation.
make_sparse(i,j,x) make_sparse - synonymous with sparse(i,j,x)
max3(x,v) max3 - synonymouse with max
nb_dims(x) nb_dims - debugged version of ndims.
peform_wiener_filtering(x0,x,... peform_wiener_filtering - perform Wiener filtering
perform_arith_coding(xC, dir) perform_arithmetic_coding_slow - perform adaptive arithmetic coding
perform_arith_fixed(x, h, n) perform_arith_fixed - arithmetic coding
perform_blurring(M, sigma, op... perform_blurring - gaussian blurs an image
perform_cg(A,y,options)
perform_convolution(x,h, boun... perform_convolution - compute convolution with centered filter.
perform_faces_reorientation(v... perform_faces_reorientation - reorient the faces with respect to the center of the mesh
perform_haar_transf(f, Jmin, ... perform_haar_transf - peform fast Haar transform
perform_hist_eq(x,y,options) perform_histogram_equalization - perform histogram equalization
perform_homotopy(D,y,options) perform_homotopy - compute the L1 regularization path
perform_huffcoding(x,T,dir) perform_huffcoding - perform huffman coding
perform_median_filtering(M,k) perform_median_filtering - perform moving average median
perform_omp(D,Y,options) perform_omp - perform orthogonal matching pursuit
perform_saturation(x,tau,use_... perform_saturation - saturate a vector for better contrast
perform_stft(x, w,q, options) perform_stft - compute a local Fourier transform
perform_tensor_decomp(T,order... perform_tensor_decomp - perform an eigendecomposition.
perform_tensor_recomp(e1,e2,l... perform_tensor_recomp - create the tensor field corresponding to the given eigendecomposition.
perform_thresholding(x, t, ty... perform_thresholding - perform hard or soft thresholding
perform_tv_denoising(x,option... perform_tv_denoising - denoising with TV minimization
perform_wavelet_transf(x, Jmi... perform_wavelet_transf - peform fast lifting transform
perform_wavortho_transf(f,Jmi... perform_wavortho_transf - compute orthogonal wavelet transform
plot_dictionnary(D,X,nb, opti... plot_dictionnary - display a dictionary of images
plot_hufftree(T,p) plot_hufftree - plot a huffman tree
plot_levelset(M,t,A) plot_levelset - display the level set of an image
plot_sparse_diracs(x, options) plot_sparse_diracs - plot sparse sets of diracs
plot_spectrogram(S,f, options) plot_spectrogram - display the spectrogram
plot_vf(vf, M, options) plot_vf - plot a vector field with
plot_wavelet(M, Jmin, options... plot_wavelet - plot 2D wavelet transform stored using Mallat's ordering.
poissrnd(lambda,m,n) POISSRND Random matrices from Poisson distribution.
progressbar(n,N,w) progressbar - display a progress bar
psnr(x,y, vmax) psnr - compute the Peack Signal to Noise Ratio
r=binornd(n,p,mm,nn) BINORND Random matrices from a binomial distribution.
radon(IMG, THETA) This MATLAB function takes an image matrix and vector of angles and then
rand_discr(p, m) rand_discr - discrete random generator
read_bin(name,options) read_bin - read bin file
rescale(x,a,b)
reverse(x) flip a vector
set_axis(v) set_axis - draw axis on/off
set_colormap(a) set_colormap - set colors for display
set_graphic_sizes(h,fs,lw) set_graphic_sizes - enlarge the size of the fonts
set_label(xstr,ystr,zstr) set_label - set the label for a plot
set_linewidth(h,lw)
set_rand_seeds(a,b) set_rand_seeds - initialize rand and randn
snr(x,y) snr - signal to noise ratio
subsampling(x,d,p) downsampling - subsampling along dimension d
subselectdim(f,sel,d) subselectdim - select along a dimension
sum3(M,k) for Scilab compatibility
tet2tri(facet, vertex, keep_s... tet2tri - convert a tet mesh to a tri mesh
upsampling(x,d,p) upsampling - add p zeros between samples along dimension d
using_matlab() using_matlab - return 1 for Matlab, 0 for Scilab
write_bin(M, name) write_bin - write a file to .bin format readable by scilab.
batch_convert_bin.m
1D Higher Order Wavelets
2D Daubechies Wavelets
Advanced Wavelet Thresholdings
Color Image Processing
Compressed Sampling
Data Dependent Noise Models
Denoising by Sobolev and Tota...
Dictionary Learning
Entropic Coding and Compressi...
Image Approximation with Orth...
Image Compression with Wavele...
Image Denoising with Linear M...
Image Denoising with Wavelets
Inpainting using Sparse Regul...
Multi-spectral Imaging
Natural Images Statistics
Non Local Means
Outliers and Median Denoiser
Reconstruction from Compressi...
Reconstruction from Partial T...
Signal Denoising with Wavelets
Signal and Image Noise Models
Sparse Deconvolution
Sparse Spikes Deconvolution w...
Sparse Spikes Deconvolution w...
Variational Inpainting
Video Coding
Volumetric wavelet Data Proce...
Wavelet Block Thresholding
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from A Numerical Tour of Signal Processing by Gabriel Peyre
A set of Matlab experiments that illustrates advanced computational signal and image processing.

snr(x,y)

function v = snr(x,y)

% snr - signal to noise ratio
%
%   v = snr(x,y);
%
% v = 20*log10( norm(x(:)) / norm(x(:)-y(:)) )
%
%   x is the original clean signal (reference).
%   y is the denoised signal.
% 
%   Copyright (c) 2008 Gabriel Peyre

v = 20*log10(norm(x(:))/norm(x(:)-y(:)));

Highlights from A Numerical Tour of Signal Processing

Highlights from
A Numerical Tour of Signal Processing