media: digital image. representing digital images ● pixel ● resolution ● aspect ratio

Media: Digital Image

Representing Digital Images

● Pixel● Resolution● Aspect ratio

Pixels

• a natural image is typically represented by a continuous or analog signal (such as a photograph, video frame, etc.)

Digital images are composed of PIXELS (or picture elements)

Pixels

• digitizing samples the natural image into discrete components

Digital images are composed of PIXELS (or picture elements)

Pixels

• each discrete sample is averaged to represent a uniform value for that area in the image

Digital images are composed of PIXELS (or picture elements)

Resolution

• PICTURE RESOLUTION is the number of pixels or samples used to represent the image

Digital images are composed of PIXELS (or picture elements)

Aspect Ratio

• ASPECT RATIO expresses this resolution as the product of the no. of horizontal pixels by the no. of vertical pixels

Digital images are composed of PIXELS (or picture elements)

Aspect Ratio

• this image is square, 50 X 50

• typical ratios are 320 X 200 or 1.6:1, 640 X 480, 800 X 600, and 1024 X 768--all of which are 1.33:1

Digital images are composed of PIXELS (or picture elements)

Aspect Ratio

• Important for scaling images or when re-sampling them at different resolutions.

• If we wish to reduce the resolution of the digital image, we must take care to preserve the same aspect ratio for it. This will ensure that it looks natural and not distorted.

Digitizing Analog Image● Analog – discrete● 2 process involved:

– Sampling– Quantizing

Sampling

● Generation of Pixels (equally same size) using grid● On the edge pixel, there are information on object and

background. Thus 2 colour exist here.● In order to represent it in digital form, pixel need to have

only one single colour● If this event occurs, the average colour will be calculated

and the entire pixel will be using this colour

Quantizing

● Process of changing the colour intensity for each pixel into exact bit colour representation

● Assign an integer value to represent the colour intensity● The range of values designated to represent the

measuring scale is the Dynamic Range.● E.g. dynamic range for digitizing a black-and-white photo

translates to how many possible level of intensity we should use to measure and represent the image

● Then this integer need to be changed into binary form

Quantizing

● The level of intensity from the brightest white to darkest black

● Normally we using 4 bit per pixel (0-15 integer)

● 1 byte = 2 pixels● Bitplanes refer to the depth

(number) of bits required for representing the image

Quantizing

• imagine a simple image with a bright object in the foreground surrounded by a dark background

QUANTIZING a sampled image refers to representing each discrete sample by a set of numbers chosen from a given scale

Quantizing

• suppose that we sampled the signal horizontally across the middle of the image

QUANTIZING a sampled image refers to representing each discrete sample by a set of numbers chosen from a given scale

Quantizing

• if we assigned a numeric scale for the signal it might look like this

QUANTIZING a sampled image refers to representing each discrete sample by a set of numbers chosen from a given scale

Dynamic Range

• Here is an intensity or graylevel image with 256 levels (i.e., 0 to 255 scale)

• 8 bits depth

DYNAMIC RANGE refers the number of values for the measuring scale used in quantizing

Dynamic Range

• Here is an intensity or graylevel image with 16 levels (i.e., 0 to 15 scale)

• 4 bits depth

DYNAMIC RANGE refers the number of values for the measuring scale used in quantizing

Dynamic Range

• Here is an intensity or graylevel image with 4 levels (i.e., 0 to 3 scale)

• 2 bits depth

DYNAMIC RANGE refers the number of values for the measuring scale used in quantizing

Dynamic Range

• Here is an intensity or graylevel image with 2 levels (i.e., 0 to 1 scale or a binary image)

• 1 bit depth

DYNAMIC RANGE refers the number of values for the measuring scale used in quantizing

How scanner works

• The document is placed on the glass plate and the cover is closed• A lamp is used to illuminate the document. The lamp in newer

scanners is either a cold cathode fluorescent lamp (CCFL) or a xenon lamp, while older scanners may have a standard fluorescent lamp.

• The entire mechanism (mirrors, lens, filter and CCD array) make up the scan head. The scan head is moved slowly across the document by a belt that is attached to a stepper motor.

• The image of the document is reflected by an angled mirror to another mirror.Each mirror is slightly curved to focus the image it reflects onto a smaller surface.

• The last mirror reflects the image onto a lens. The lens focuses the image through a filter on the CCD array.

CCD

• As photo sensor

• CCDs use a special manufacturing process to create the ability to transport charge across the chip without distortion. This process leads to very high-quality sensors in terms of fidelity and light sensitivity

• CCD sensors create high-quality, low-noise images

CCD: Advantages

• Output voltage by CCD has reflects the number of charge collected from each pixel

• Really sensitive even a slight changes in colour intensity – more accurate

• No noise effects• CCD sensors have been mass produced for a longer

period of time, so they are more mature. They tend to have higher quality and more pixels.

Factors: Low Quality output for digital image• Choosing a low resolution

– Blocky image

• Dynamic Range is low– Affects the image’s contour colour

• Scanner – Noise when scanning will produce low quality image

Colour Representation: RGB• RGB color model

employs additive primaries

• RGB color is employed by most color video displays

• (0,0,0) = black

• (1,1,1) = white

Colour Representation: CMYK

• CMYK is based on subtractive primaries (paint pigments)

• is used for printing• employs BLACK (K) for

highlights and details (printing purpose)

The CMYK color model employs four channels to create color: CYAN, MAGENTA, YELLOW, and BLACK

Colour Representation: CMYK

• Here is a CMYK image

• again, we will separate it into four channels

The CMYK color model employs four channels to create color: CYAN, MAGENTA, YELLOW, and BLACK

Colour Representation: HSB

• HSB resembles how artists conceive color properties• HSB color is depicted by a 3-D polar coordinate

system• Hue

– Color wheel• Saturation

– The strength of hue– Pastels are partially saturated– Vivid colors are deeply saturated

• Brightness/Lightness– Lightness or darkness of the shade

HSB color is defined by three separate values: HUE, SATURATION, and BRIGHTNESS

Colour Representation: HSB

• A single hue value is depicted with a series of changing brightness and saturation values

HSB color is defined by three separate values: HUE, SATURATION, and BRIGHTNESS

Displaying Digital Image• Depends on

– Bit depth or Colour Resolution– Output Resolution– Image Resolution

Colour Resolution (Bit Depth)

• Referring to the number of bit used per pixel to represent the colour used

• 1 bit, 4 bit up to 32 bit• Number of bit , image quality

Output Resolution (Screen) Referring to the number of dots per inch (dpi) used for

output device (monitor, LCP panel, video/data projector) Normal monitor resolution is 72 dpi

Image Resolution

• Referring to the number of pixel consists in the image• Pixel per inch (ppi)• PPI , quality , size , processing time

Storing Digital Images

• INDEXED COLOR images are derived from full color images

• INDEXED COLOR images are smaller or more compact in storage

• are composed of pixels selected from a limited palette of colors or shades

Storing Digital Images● Digital images are converted to files for storage

and transfer● The file type is a special format for ordering and

storing the bytes that make up the image● File types or formats are not necessarily

compatible● You must often match the file type with the

application

Storing Digital Images● TIFF (Tagged Image File Format)

– used by most document preparation programs– has optional lossless compression– Windows and Macintosh formats differ

● GIF (Graphic Interchange Format)– indexed color image (up to 256 colors)– compressed– used in Web applications

Storing Digital Images● JPEG (Joint Photographic Experts Group)

– lossy compression with variable controls– also used in Web applications

● PNG (Portable Network Graphics)– To replace GIF & TIFF– alpha channels (variable transparency), gamma

correction (cross-platform control of image brightness), and two-dimensional interlacing (a method of progressive display)

● WMF (Windows Metafile Format)– “metafile” formats permit a variety of image types

● PICT– the metafile format for Macintosh apps

8 common image formats

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