Linear combination of images

`Z = imlincomb(K1,A1,K2,A2,...,Kn,An)`

Z = imlincomb(K1,A1,K2,A2,...,Kn,An,K)

Z = imlincomb(___,output_class)

gpuarrayZ = imlincomb(gpuarrayK,gpuarrayA,___,output_class)

`Z = imlincomb(K1,A1,K2,A2,...,Kn,An)`

computes

K1*A1 + K2*A2 + ... + Kn*An

where `K1`

, `K2`

, through `Kn`

are
real, double scalars and `A1`

, `A2`

,
through `An`

are real, nonsparse, numeric arrays
with the same class and size. `Z`

has the same class
and size as `A1`

unless `A1`

is
logical, in which case `Z`

is double.

`Z = imlincomb(K1,A1,K2,A2,...,Kn,An,K)`

computes

K1*A1 + K2*A2 + ... + Kn*An + K

where `imlincomb`

adds `K`

,
a real, double scalar, to the sum of the products of `K1`

through `Kn`

and `A1`

through `An`

.

`Z = imlincomb(___,output_class)`

lets
you specify the class of `Z`

. `output_class`

is
a character vector containing the name of a numeric class.

`gpuarrayZ = imlincomb(gpuarrayK,gpuarrayA,___,output_class)`

performs
the operation on a GPU, where the input values,`gpuarrayK`

and `gpuarrayA`

,
are gpuArrays and the output value, `gpuarrayZ`

is
a gpuArray. This syntax requires the Parallel Computing Toolbox™

When performing a series of arithmetic operations on a pair
of images, you can achieve more accurate results if you use `imlincomb`

to
combine the operations, rather than nesting calls to the individual
arithmetic functions, such as `imadd`

. When you nest
calls to the arithmetic functions, and the input arrays are of an
integer class, each function truncates and rounds the result before
passing it to the next function, thus losing accuracy in the final
result. `imlincomb`

computes each element of the
output `Z`

individually, in double-precision floating
point. If `Z`

is an integer array, `imlincomb`

truncates
elements of `Z`

that exceed the range of the integer
type and rounds off fractional values.

Code Generation support: Yes.

MATLAB Function Block support: Yes.

Scale an image by a factor of `2`

.

I = imread('cameraman.tif'); J = imlincomb(2,I); imshow(J)

Scale an image by a factor of `2`

, performing
the operation on a GPU.

I = gpuArray(imread('cameraman.tif')); J = imlincomb(2,I); imshow(J)

Form a difference image with the zero value shifted to `128`

.

I = imread('cameraman.tif'); J = uint8(filter2(fspecial('gaussian'), I)); K = imlincomb(1,I,-1,J,128); % K(r,c) = I(r,c) - J(r,c) + 128 figure, imshow(K)

Form a difference image with the zero value shifted to `128`

,
performing the operation on a GPU.

I = gpuArray(imread('cameraman.tif')); J = uint8(filter2(fspecial('gaussian'), I)); K = imlincomb(1,I,-1,J,128); % K(r,c) = I(r,c) - J(r,c) + 128 figure, imshow(K)

Add two images with a specified output class.

I = imread('rice.png'); J = imread('cameraman.tif'); K = imlincomb(1,I,1,J,'uint16'); figure, imshow(K,[])

Add two images with a specified output class.

I = gpuArray(imread('rice.png')); J = gpuArray(imread('cameraman.tif')); K = imlincomb(1,I,1,J,'uint16'); figure, imshow(K,[])

To illustrate how `imlincomb`

performs all
the arithmetic operations before truncating the result, compare the
results of calculating the average of two arrays, `X`

and `Y`

,
using nested arithmetic functions and then using `imlincomb`

.

In the version that uses nested arithmetic functions, `imadd`

adds `255`

and `50`

and
truncates the result to `255`

before passing it to `imdivide`

.
The average returned in `Z(1,1)`

is `128`

.

X = uint8([ 255 10 75; 44 225 100]); Y = uint8([ 50 20 50; 50 50 50 ]); Z = imdivide(imadd(X,Y),2) Z = 128 15 63 47 128 75

`imlincomb`

performs the addition and division
in double precision and only truncates the final result. The average
returned in `Z2(1,1)`

is `153`

.

Z2 = imlincomb(.5,X,.5,Y) Z2 = 153 15 63 47 138 75

`gpuArray`

| `imadd`

| `imcomplement`

| `imdivide`

| `immultiply`

| `imsubtract`

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