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Image Formation Fundamentals
CS491E/791E
How are images represented
in the computer?
Color images
Image formation
• There are two parts to the image formation process:
– The geometry of image formation, which determines where
in the image plane the projection of a point in the scene will
be located.
– The physics of light, which determines the brightness of a
point in the image plane as a function of illumination and
surface properties.
A Simple model of image formation
• The scene is illuminated by a single source.
• The scene reflects radiation towards the camera.
• The camera senses it via chemicals on film.
Pinhole camera
• This is the simplest device to form an image of a 3D scene
on a 2D surface.
• Straight rays of light pass through a “pinhole” and form an
inverted image of the object on the image plane.
fX
x
Z
=
fY
y
Z
=
Camera optics
• In practice, the aperture must be larger to admit more light.
• Lenses are placed to in the aperture to focus the bundle of rays
from each scene point onto the corresponding point in the image
plane
Image formation (cont’d)
• Optical parameters of the lens
– lens type
– focal length
– field of view
• Photometric parameters
– type, intensity, and direction of illumination
– reflectance properties of the viewed surfaces
• Geometric parameters
– type of projections
– position and orientation of camera in space
– perspective distortions introduced by the imaging process
Image distortion
What is light?
• The visible portion of the electromagnetic (EM)
spectrum.
• It occurs between wavelengths of approximately 400 and
700 nanometers.
Short wavelengths
• Different wavelengths of radiation have different
properties.
• The x-ray region of the spectrum, it carries sufficient
energy to penetrate a significant volume or material.
Long wavelengths
• Copious quantities of infrared (IR) radiation are emitted
from warm objects (e.g., locate people in total darkness).
Long wavelengths (cont’d)
• “Synthetic aperture radar” (SAR) imaging techniques
use an artificially generated source of microwaves to probe
a scene.
• SAR is unaffected by weather conditions and clouds (e.g.,
has provided us images of the surface of Venus).
Range images
• An array of distances to the objects in the scene.
• They can be produced by sonar or by using laser
rangefinders.
Sonic images
• Produced by the reflection of sound waves off an object.
• High sound frequencies are used to improve resolution.
CCD (Charged-Coupled Device) cameras
• Tiny solid state cells convert light energy into electrical
charge.
• The image plane acts as a digital memory that can be read
row by row by a computer.
Frame grabber
• Usually, a CCD camera plugs into a computer board
(frame grabber).
• The frame grabber digitizes the signal and stores it in its
memory (frame buffer).
Image digitization
• Sampling means measuring the value of an image at a
finite number of points.
• Quantization is the representation of the measured value
at the sampled point by an integer.
Image digitization (cont’d)
Image quantization(example)
• 256 gray levels (8bits/pixel) 32 gray levels (5 bits/pixel) 16 gray levels (4 bits/pixel)
• 8 gray levels (3 bits/pixel) 4 gray levels (2 bits/pixel) 2 gray levels (1 bit/pixel)
Image sampling (example)
original image sampled by a factor of 2
sampled by a factor of 4 sampled by a factor of 8
Digital image
• An image is represented by a rectangular array of integers.
• An integer represents the brightness or darkness of the
image at that point.
• N: # of rows, M: # of columns, Q: # of gray levels
– N = , M = , Q = (q is the # of bits/pixel)
– Storage requirements: NxMxQ (e.g., N=M=1024, q=8, 1MB)
(0,0) (0,1) ... (0, 1)
(1,0) (1,1) ... (1, 1)
... ... ... ...
( 1,0) ( 1,1) ... ( 1, 1)
f f f M
f f f M
f N f N f N M
−
−
− − − −
2 n 2 m 2 q
Image file formats
• Many image formats adhere to the simple model shown below
(line by line, no breaks between lines).
• The header contains at least the width and height of the image.
• Most headers begin with a signature or “magic number” - a
short sequence of bytes for identifying the file format.
Common image file formats
• GIF (Graphic Interchange Format) -
• PNG (Portable Network Graphics)
• JPEG (Joint Photographic Experts Group)
• TIFF (Tagged Image File Format)
• PGM (Portable Gray Map)
• FITS (Flexible Image Transport System)
Comparison of image formats
PGM format
• A popular format for grayscale images (8 bits/pixel)
• Closely-related formats are:
– PBM (Portable Bitmap), for binary images (1 bit/pixel)
– PPM (Portable Pixelmap), for color images (24 bits/pixel)
• ASCII or binary (raw) storage
ASCII vs Raw format
• ASCII format has the following advantages:
– Pixel values can be examined or modified very easily using a
standard text editor.
– Files in raw format cannot be modified in this way since they
contain many unprintable characters.
• Raw format has the following advantages:
– It is much more compact compared to the ASCII format.
– Pixel values are coded using only a single character !
Image Class
class ImageType {
public:
ImageType();
~ImageType();
// more functions ...
private:
int N, M, Q; //N: # rows, M: # columns
int **pixelValue;
};
An example - Threshold.cpp
void readImageHeader(char[], int&, int&, int&, bool&);
void readImage(char[], ImageType&);
void writeImage(char[], ImageType&);
void main(int argc, char *argv[])
{
int i, j;
int M, N, Q;
bool type;
int val;
int thresh;
// read image header
readImageHeader(argv[1], N, M, Q, type);
// allocate memory for the image array
ImageType image(N, M, Q);
// read image
readImage(argv[1], image);
Threshold.cpp (cont’d)
cout << "Enter threshold: ";
cin >> thresh;
// threshold image
for(i=0; i<N; i++)
for(j=0; j<M; j++) {
image.getVal(i, j, val);
if(val < thresh)
image.setVal(i, j, 255);
else
image.setVal(i, j, 0);
}
// write image
writeImage(argv[2], image);
}
Reading/Writing PGM images
Writing a PGM image to a file
void writeImage(char fname[], ImageType& image)
int N, M, Q;
unsigned char *charImage;
ofstream ofp;
image.getImageInfo(N, M, Q);
charImage = (unsigned char *) new unsigned char [M*N];
// convert the integer values to unsigned char
int val;
for(i=0; i<N; i++)
for(j=0; j<M; j++)
image.getVal(i, j, val);
charImage[i*M+j]=(unsigned char)val;
}
Writing a PGM image... (cont’d)
ofp.open(fname, ios::out);
if (!ofp) {
cout << "Can't open file: " << fname << endl;
exit(1);
}
ofp << "P5" << endl;
ofp << M << " " << N << endl;
ofp << Q << endl;
ofp.write( reinterpret_cast<char *>(charImage), (M*N)*sizeof(unsigned char));
if (ofp.fail()) {
cout << "Can't write image " << fname << endl;
exit(0);
}
ofp.close();
}
Reading a PGM image from a file
void readImage(char fname[], ImageType& image)
{
int i, j;
int N, M, Q;
unsigned char *charImage;
char header [100], *ptr;
ifstream ifp;
ifp.open(fname, ios::in);
if (!ifp) {
cout << "Can't read image: " << fname << endl;
exit(1);
}
// read header
ifp.getline(header,100,'n');
if ( (header[0]!=80) || /* 'P' */
(header[1]!=53) ) { /* '5' */
cout << "Image " << fname << " is not PGM" << endl;
exit(1);
}
Reading a PGM image …. (cont’d)
ifp.getline(header,100,'n');
while(header[0]=='#')
ifp.getline(header,100,'n');
M=strtol(header,&ptr,0);
N=atoi(ptr);
ifp.getline(header,100,'n');
Q=strtol(header,&ptr,0);
charImage = (unsigned char *) new unsigned char [M*N];
ifp.read( reinterpret_cast<char *>(charImage), (M*N)*sizeof(unsigned char));
if (ifp.fail()) {
cout << "Image " << fname << " has wrong size" << endl;
exit(1);
}
ifp.close();
Reading a PGM image…(cont’d)
//
// Convert the unsigned characters to integers
//
int val;
for(i=0; i<N; i++)
for(j=0; j<M; j++) {
val = (int)charImage[i*M+j];
image.setVal(i, j, val);
}
}
How do I “see” images on the computer?
• Unix: xv, gimp
• Windows: Photoshop
How do I display an image from within
my C++ program?
• Save the image into a file with a default name (e.g., tmp.pgm)
using the WriteImage function.
• Put the following command in your C++ program:
system(“xv tmp.pgm”);
• This is a system call !!
• It passes the command within the quotes to the Unix operating
system.
• You can execute any Unix command this way ….
How do I convert an image from one
format to another?
• Use xv’s “save” option
• It can also convert images
How do I print an image?
• Load the image using “xv”
• Save the image in “postscript” format
• Print the postscript file (e.g., lpr -Pname image.ps)
Image processing software
• CVIPtools (Computer Vision and Image Processing tools)
• Intel Open Computer Vision Library
• Microsoft Vision SDL Library
• Matlab
• Khoros
• For more information, see
– http://www.cs.unr.edu/~bebis/CS791E
– http://www.cs.unr.edu/CRCD/ComputerVision/cv_resources.html

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Ip fundamentals(3)-edit7

  • 2. How are images represented in the computer?
  • 4. Image formation • There are two parts to the image formation process: – The geometry of image formation, which determines where in the image plane the projection of a point in the scene will be located. – The physics of light, which determines the brightness of a point in the image plane as a function of illumination and surface properties.
  • 5. A Simple model of image formation • The scene is illuminated by a single source. • The scene reflects radiation towards the camera. • The camera senses it via chemicals on film.
  • 6. Pinhole camera • This is the simplest device to form an image of a 3D scene on a 2D surface. • Straight rays of light pass through a “pinhole” and form an inverted image of the object on the image plane. fX x Z = fY y Z =
  • 7. Camera optics • In practice, the aperture must be larger to admit more light. • Lenses are placed to in the aperture to focus the bundle of rays from each scene point onto the corresponding point in the image plane
  • 8. Image formation (cont’d) • Optical parameters of the lens – lens type – focal length – field of view • Photometric parameters – type, intensity, and direction of illumination – reflectance properties of the viewed surfaces • Geometric parameters – type of projections – position and orientation of camera in space – perspective distortions introduced by the imaging process
  • 10. What is light? • The visible portion of the electromagnetic (EM) spectrum. • It occurs between wavelengths of approximately 400 and 700 nanometers.
  • 11. Short wavelengths • Different wavelengths of radiation have different properties. • The x-ray region of the spectrum, it carries sufficient energy to penetrate a significant volume or material.
  • 12. Long wavelengths • Copious quantities of infrared (IR) radiation are emitted from warm objects (e.g., locate people in total darkness).
  • 13. Long wavelengths (cont’d) • “Synthetic aperture radar” (SAR) imaging techniques use an artificially generated source of microwaves to probe a scene. • SAR is unaffected by weather conditions and clouds (e.g., has provided us images of the surface of Venus).
  • 14. Range images • An array of distances to the objects in the scene. • They can be produced by sonar or by using laser rangefinders.
  • 15. Sonic images • Produced by the reflection of sound waves off an object. • High sound frequencies are used to improve resolution.
  • 16. CCD (Charged-Coupled Device) cameras • Tiny solid state cells convert light energy into electrical charge. • The image plane acts as a digital memory that can be read row by row by a computer.
  • 17. Frame grabber • Usually, a CCD camera plugs into a computer board (frame grabber). • The frame grabber digitizes the signal and stores it in its memory (frame buffer).
  • 18. Image digitization • Sampling means measuring the value of an image at a finite number of points. • Quantization is the representation of the measured value at the sampled point by an integer.
  • 20. Image quantization(example) • 256 gray levels (8bits/pixel) 32 gray levels (5 bits/pixel) 16 gray levels (4 bits/pixel) • 8 gray levels (3 bits/pixel) 4 gray levels (2 bits/pixel) 2 gray levels (1 bit/pixel)
  • 21. Image sampling (example) original image sampled by a factor of 2 sampled by a factor of 4 sampled by a factor of 8
  • 22. Digital image • An image is represented by a rectangular array of integers. • An integer represents the brightness or darkness of the image at that point. • N: # of rows, M: # of columns, Q: # of gray levels – N = , M = , Q = (q is the # of bits/pixel) – Storage requirements: NxMxQ (e.g., N=M=1024, q=8, 1MB) (0,0) (0,1) ... (0, 1) (1,0) (1,1) ... (1, 1) ... ... ... ... ( 1,0) ( 1,1) ... ( 1, 1) f f f M f f f M f N f N f N M − − − − − − 2 n 2 m 2 q
  • 23. Image file formats • Many image formats adhere to the simple model shown below (line by line, no breaks between lines). • The header contains at least the width and height of the image. • Most headers begin with a signature or “magic number” - a short sequence of bytes for identifying the file format.
  • 24. Common image file formats • GIF (Graphic Interchange Format) - • PNG (Portable Network Graphics) • JPEG (Joint Photographic Experts Group) • TIFF (Tagged Image File Format) • PGM (Portable Gray Map) • FITS (Flexible Image Transport System)
  • 26. PGM format • A popular format for grayscale images (8 bits/pixel) • Closely-related formats are: – PBM (Portable Bitmap), for binary images (1 bit/pixel) – PPM (Portable Pixelmap), for color images (24 bits/pixel) • ASCII or binary (raw) storage
  • 27. ASCII vs Raw format • ASCII format has the following advantages: – Pixel values can be examined or modified very easily using a standard text editor. – Files in raw format cannot be modified in this way since they contain many unprintable characters. • Raw format has the following advantages: – It is much more compact compared to the ASCII format. – Pixel values are coded using only a single character !
  • 28. Image Class class ImageType { public: ImageType(); ~ImageType(); // more functions ... private: int N, M, Q; //N: # rows, M: # columns int **pixelValue; };
  • 29. An example - Threshold.cpp void readImageHeader(char[], int&, int&, int&, bool&); void readImage(char[], ImageType&); void writeImage(char[], ImageType&); void main(int argc, char *argv[]) { int i, j; int M, N, Q; bool type; int val; int thresh; // read image header readImageHeader(argv[1], N, M, Q, type); // allocate memory for the image array ImageType image(N, M, Q); // read image readImage(argv[1], image);
  • 30. Threshold.cpp (cont’d) cout << "Enter threshold: "; cin >> thresh; // threshold image for(i=0; i<N; i++) for(j=0; j<M; j++) { image.getVal(i, j, val); if(val < thresh) image.setVal(i, j, 255); else image.setVal(i, j, 0); } // write image writeImage(argv[2], image); }
  • 32. Writing a PGM image to a file void writeImage(char fname[], ImageType& image) int N, M, Q; unsigned char *charImage; ofstream ofp; image.getImageInfo(N, M, Q); charImage = (unsigned char *) new unsigned char [M*N]; // convert the integer values to unsigned char int val; for(i=0; i<N; i++) for(j=0; j<M; j++) image.getVal(i, j, val); charImage[i*M+j]=(unsigned char)val; }
  • 33. Writing a PGM image... (cont’d) ofp.open(fname, ios::out); if (!ofp) { cout << "Can't open file: " << fname << endl; exit(1); } ofp << "P5" << endl; ofp << M << " " << N << endl; ofp << Q << endl; ofp.write( reinterpret_cast<char *>(charImage), (M*N)*sizeof(unsigned char)); if (ofp.fail()) { cout << "Can't write image " << fname << endl; exit(0); } ofp.close(); }
  • 34. Reading a PGM image from a file void readImage(char fname[], ImageType& image) { int i, j; int N, M, Q; unsigned char *charImage; char header [100], *ptr; ifstream ifp; ifp.open(fname, ios::in); if (!ifp) { cout << "Can't read image: " << fname << endl; exit(1); } // read header ifp.getline(header,100,'n'); if ( (header[0]!=80) || /* 'P' */ (header[1]!=53) ) { /* '5' */ cout << "Image " << fname << " is not PGM" << endl; exit(1); }
  • 35. Reading a PGM image …. (cont’d) ifp.getline(header,100,'n'); while(header[0]=='#') ifp.getline(header,100,'n'); M=strtol(header,&ptr,0); N=atoi(ptr); ifp.getline(header,100,'n'); Q=strtol(header,&ptr,0); charImage = (unsigned char *) new unsigned char [M*N]; ifp.read( reinterpret_cast<char *>(charImage), (M*N)*sizeof(unsigned char)); if (ifp.fail()) { cout << "Image " << fname << " has wrong size" << endl; exit(1); } ifp.close();
  • 36. Reading a PGM image…(cont’d) // // Convert the unsigned characters to integers // int val; for(i=0; i<N; i++) for(j=0; j<M; j++) { val = (int)charImage[i*M+j]; image.setVal(i, j, val); } }
  • 37. How do I “see” images on the computer? • Unix: xv, gimp • Windows: Photoshop
  • 38. How do I display an image from within my C++ program? • Save the image into a file with a default name (e.g., tmp.pgm) using the WriteImage function. • Put the following command in your C++ program: system(“xv tmp.pgm”); • This is a system call !! • It passes the command within the quotes to the Unix operating system. • You can execute any Unix command this way ….
  • 39. How do I convert an image from one format to another? • Use xv’s “save” option • It can also convert images
  • 40. How do I print an image? • Load the image using “xv” • Save the image in “postscript” format • Print the postscript file (e.g., lpr -Pname image.ps)
  • 41. Image processing software • CVIPtools (Computer Vision and Image Processing tools) • Intel Open Computer Vision Library • Microsoft Vision SDL Library • Matlab • Khoros • For more information, see – http://www.cs.unr.edu/~bebis/CS791E – http://www.cs.unr.edu/CRCD/ComputerVision/cv_resources.html