reconstructImage: Reconstructing an image from a patch decomposition

In MBCbook: Companion Package for the Book "Model-Based Clustering and Classification for Data Science" by Bouveyron et al. (2019, ISBN:9781108644181).

Description

A simple way of reconstructing an image from a patch decomposition.

Usage

reconstructImage(X,nl,nc)

Arguments

X	the matrix of patches to be used for reconstructing the image.
nl	the number of rows of the image.
nc	the number of columns of the image.

Value

an image is returned as a matrix object, that can be display with the imshow function.

Author(s)

C. Bouveyron & J. Delon

Examples

Im = diag(16) 
ImNoise = Im + rnorm(256,0,0.1)
X = imageToPatch(ImNoise,4)
out = mixmodCluster(X,10,model=mixmodGaussianModel(family=c("spherical")))
res = mixmodPredict(X,out@bestResult)
Xdenoised = denoisePatches(X,out,P = res@proba,sigma = 0.1) 
ImRec = reconstructImage(Xdenoised,16,16)
par(mfrow=c(1,3)); imshow(Im); imshow(ImNoise); imshow(ImRec)

Example output

Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: Rmixmod
Loading required package: Rcpp
Rmixmod v. 2.1.5 / URI: www.mixmod.org
Loading required package: MASS
Loading required package: mvtnorm

Attaching package: ‘mvtnorm’

The following object is masked from ‘package:mclust’:

    dmvnorm

MBCbook documentation built on July 2, 2019, 9:08 a.m.