INTRODUCCIÓN AL PROCESADO DE IMAGEN

TEMA 2

INTRODUCCIÓN A LA IMAGEN DIGITAL

ADQUISICIÓN Y FORMACIÓN

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Image FormationImage Formation

objec

t

image plane

lens

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Image FormationImage Formationlig

ht so

urce

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Image FormationImage Formation

projection through lens

projection through lens

image of objectimage of object

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Image FormationImage Formation

projection onto discrete sensor

array.

projection onto discrete sensor

array. digital cameradigital camera

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Image FormationImage Formation

sensors register average color.

sensors register average color.

sampled imagesampled image

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Image FormationImage Formation

continuous colors, discrete locations.

continuous colors, discrete locations.

discrete real-valued image

discrete real-valued image

MUESTREO Y CUANTIFICACIÓN

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Sampling and Quantization

pixel grid

sampledreal image quantized sampled & quantized

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Sampling and Quantization

sampledreal image quantized sampled & quantized

pixel gridcolumn indexcolumn index

row

inde

xro

w in

dex

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Sampling

pixel grid

),( crI S ,CI

sampled image

Take the average within each square.

Take the average within each square.

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Sampling

),( crI S ,CI

continuous image sampled image

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Sampling

),( crI S ,CI

sampled image

Take the average within each square.

Take the average within each square.

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Sampling

Efectos del muestreo espacial:

•Teóricamente, bajo ciertas condiciones (las del teorema de muestreo), no hay pérdida de información en el muestreo.

•En la práctica, el muestreo limita la resolución de la imagen.

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continuous color input

disc

rete

col

or o

utpu

t

continuous colors mapped to a finite,

discrete set of colors.

continuous colors mapped to a finite,

discrete set of colors.

Quantification

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Cuantificación

Efecto de la cuantificación

•Si el número de niveles de intensidad usados para representar una imagen monocromo es pequeño, el ojo puede detectar efectos de contorno en el objeto•En el caso de imágenes B&W, con pocos tonos se observa ya alta calidad (con 100 niveles es suficiente, con 64 es muchas veces admisible)

32 niveles 16 niveles

8 niveles 4 niveles

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8 bits 256 levels 7 bits 128 levels 6 bits 64 levels 5 bits 32 levels

4 bits 16 levels 3 bits 8 levels 2 bits 4 levels 1 bit 2 levels

Cuantificación

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Intensity Quantization

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Cuantificación

•El tamaño de la “paleta de colores” (es decir, el número de colores utilizados para representar cada píxel es otro factor determinante de la calidad.

•Si este número es muy bajo, se apreciarán contornos artificiales que resultan visualmente molestos.

•Suelen ser necesarios 24 bits (3x8) ó 16 millones de colores (color real) para una visualización perfecta, con una paleta de 16 bits ó 65556 colores se aprecia casi sin distorsión, pero con una paleta de 8 bits ó 256 colores la calidad se ve muy deteriorada y con 16 la imagen es inservible).

16 mill

256

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Resampling

8× 16×nearest neighbornearest neighbor nearest neighbornearest neighbor

bicubic interpolationbicubic interpolation bicubic interpolationbicubic interpolation

(resizing)

IMAGEN DIGITAL

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Digital ImageDigital Image

a grid of squares, each of which

contains a single color

a grid of squares, each of which

contains a single color

each square is called a pixel (for picture element)

each square is called a pixel (for picture element)

Color images have 3 values per pixel; monochrome images have 1

value per pixel.

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A digital image, I, is a mapping from a 2D grid of uniformly spaced discrete points, {p = (r,c)}, into a set of positive integer values, {I( p)}, or a set of vector values, e.g., {[R G B]T(p)}.

At each column location in each row of I there is a value.

The pair ( p, I( p) ) is called a “pixel” (for picture element).

Pixels

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p = (r,c) is the pixel location indexed by row, r, and column, c.

I( p) = I(r,c) is the value of the pixel at location p.If I( p) is a single number then I is monochrome.If I( p) is a vector (ordered list of numbers) then I

has multiple bands (e.g., a color image).

Pixels

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Pixel Location: p = (r , c)

Pixel Value: I(p) = I(r , c) Pixel : [ p, I(p)]

Pixels

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Pixel : [ p, I(p)]Pixels

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Color Images

Are constructed from three intensity maps.

Each intensity map is pro-jected through a color filter (e.g., red, green, or blue, or cyan, magenta, or yellow) to create a monochrome image.

The intensity maps are overlaid to create a color image.

Each pixel in a color image is a three element vector.

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Color Images On a CRT*

Color Images On a CRT*

* Tubo de rayos catódicos

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Point ProcessingPoint Processing

original + gamma- gamma + brightness- brightness

original + contrast- contrast histogram EQhistogram mod

PERCEPCIÓN DEL COLOR (2)

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luminan

cehue

saturation

photo receptorsbrain

The eye has 3 types of photoreceptors: sensitive to red, green, or blue light.

The brain transforms RGB into separate brightness and color channels (e.g., LHS).

Color Sensing / Color Perception

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Color Perception

all bandsall bands luminanceluminance chrominancechrominance

redred greengreen blueblue

16× pixelization of:

luminance and chrominance (hue+saturation) are perceived with different resolutions, as are red, green and blue.

luminance and chrominance (hue+saturation) are perceived with different resolutions, as are red, green and blue.

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Color Balance and Saturation

Uniform changes in color components result in change of tint.

E.g., if all G pixel values are multiplied by > 1 then the image takes a green cast.

ALGUNAS OPERACIONES SOBRE IMAGEN

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Rotation

and motion blur

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Image Warping

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originalblurred sharpened

Spatial Filtering

FORMATOS DE IMAGEN

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Formatos de Imagen

Clasificación según el número de bandas o canales:•En color (RGB): se almacena RGB de alguna forma.•En escala de grises: se almacena Y de alguna forma.•Binarias: sólo existen dos colores, el blanco y el negro. Su origen suele ser el procesado de otras imágenes (ej: OCR’s).•Multi-canal: se almacenan más de 3 canales, típico en sensoresmulti-e hiper-espectrales para aplicaciones de observación terrestre.

JPEG

GIF

TIFF

PNG

BMP

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Image Compression: JPEGJP

EG

qua

lity

leve

lF

ile size in bytes

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JPE

G q

uali

ty le

vel

File size in

bytes

INTRODUCCIÓN AL PROCESADO DE IMAGEN

TEMA 2

INTRODUCCIÓN A LA IMAGEN DIGITAL