DIGITAL DATA Danny M . Vaughn, Ph.D., CM S

Introduction To develop an image that represents brightness values represented in digital form. As a result, arithmetic operations may be employed to enhance the final image. Began in 1972 w/ LANDSAT 1.

Accomplished by machine processing (computer-assisted). Often faster & more sophisticated analysis. Enables large, synoptic scale images to be analyzed.

Still requires an understanding for earth-surface expressions.

Advantages Cost effective for large geographic areas. Cost effective for repetitive interpretations. Cost effective for standard image formats (LANDSAT,SPOT). Consistent results. Simultaneous interpretations of several channels (bands).

Complex interpretation algorithms possible. Speed as an advantage w/ large data sets. Explore alternatives in enhancement. Compatible w/ other digital data.

Disadvantages Expensive for small areas. Expensive for one-time interpretations. High start-up costs. Requires elaborate, single purpose equipment.

Accuracy may be difficult to evaluate. Requires standard image formats. Data may be expensive, or not available. Preprocessing may be required. M ay require large support staff.

Im age Analysis Process Space sensors measure reflected/emitted radiation from theearth's surface. Energy for surface features does not represent an exactspectral signature as atmospheric scattering, and attenuationoccur. Based upon interaction between surface features (number,size, & shapes); and radiometric, spectral, & spatial resolutionof a sensor.

Brightness values dependent upon, time of year, latitude,solar angle, solar elevation, topography, slope, aspect, &relief.

M ay produce a pictorial image or an array of digital(brightness) values.

Digital analysis allows analysis from multiple channels, &relies upon digital brightness values for an objective, abstract,quantitative assessment. Manual interpretation requires experience, is subjective,concrete, and qualitative.

Typical sequence for digital analysis

Preprocessng

Histograms, scattergrams, statistical summaries. Correct for radiometric errors (scattering, scan angle variations,variations in illumination, & system noise).

A Also correct for geometric errors (scale, projection, & platformdeviations).

F eature extraction - Reduce the dimensionality of a data set(principal components analysis).

Image enhancement

Histogram equalization, contrast stretch, ratios, & otherarithmetic operations. Do not classify from an enhanced image, digital values are notproportionally adjusted. M ay interpret manually for training selection & classification.

Selection of training data - Brightness values indicative of selectsurface features.

Classification decision

Select surface features w/ same brightness values. Supervised Classification - Analyst selects training samples/features be consistent brightness values.

Unsupervised Classification - Algorithm selects by statisticalgroups. Analyst must next determine if the groups correspond toa particular surface feature(s). Classification output - As alphanumeric map w/ classesassigned.Assess accuracy - Ground truth, maps, photographs,documents, etc. Create final classification and print map, data,& reports.

Digital Data Electro-optical scanner (LANDSAT, SPOT) measures relativebrightness about the earth's surface in several bands. Each current (for each band) represents a continuous variation(analog) of signals. The current is sampled at uniform intervals by analog to digitalconversion (A-to-D). Each digital value is recorded as a series of binary digits orbits, w/each bit recording an exponent of a power 2.

The value of the exponent is determined by the position on thebit in a sequence. Six bits - 25 + 24 + 23 + 22 + 21 + 20 = 32 + 16 + 8 + 4 + 2 + 1 =

63 (0 to 63 = 64 brightness levels). Seven bits - 26 + 25 + 24 + 23 + 22 + 21 + 20 = 64 + 32 + 16 + 8 +4 + 2 + 1 = 127 (0 to 127 = 128 brightness levels). Eight bits - 27 + 26 + 25 + 24 + 23 + 22 + 21 + 20 = 128 + 64 + 32+ 16 + 8 + 4 + 2 + 1 = 255 (0 to 255 = 256 brightness levels). Six binary places are available to record the brightness sensedfor each band. e.g. 110100, equates to: 25 + 24 + 03 + 22 + 01 + 00= 32 + 16 + 0 + 4 + 0 = 52.

Discrete brightness (absolute) values are recorded for eachpixel. The greater the number of bits (5, 6, 7, 8), the higher theradiometric resolution (brightness values per pixel). W hen increasing bits per pixel w/ transmission & storage heldconstant, there are fewer pixels per image w/ larger pixel sizes(decreased spatial resolution). The radiometric resolution is controlled by the sensitivity of thesensor system.

Tape Form ats Band Interleaved by Pixel (BIP) Computer tape records in sequence brightness values for line1, pixel 1, band 1; line 1, pixel 1, band 2; line 1, pixel 1, band 3;line 1, pixel 1, band 4. Next line 1, pixel 2, band 1; line 1, pixel 2, band 2; line 1,pixel 2, band 3; line 1, pixel 2, and band 4.

All brightness values for all bands are written to the tapebefore the values for the next pixel are written.

M ust assess all data to sort the bands into respectiveimages. Advantage if you know the exact position of a sub-area,values for all bands are together. Inconvenient & awkward, must read four panels toreconstruct all bands for the entire scene.

Band Interleaved by Line (BIL) Each line as a separate unit; line 1, band 1, line 1, band 2, line1, band 3, line 1, band 4. Each line is represented in all four bands. Good for viewing all bands of an entire scene.

Band Sequential (BSQ) All data for band 1 are written in sequence, followed by band 2,band 3, etc. Begin with row 1, column (pixel) 1, move to right through allpixels in row 1, followed by row 2, pixel 1, etc. Each band as a separate unit. Good for viewing all bands of an entire scene. All use raster data structures.

Hardware Requirem ents.

Computers

CPU - Heart of computer. Control unit - M anages flow of data & instructions to CPU &to & from output devices. Arithmetic/logic unit - M anipulates input data to produceoutput values yielding results for an operation. Primary storage - RAM (random access m emory) with nosequential searching. Data is stored in binary form & a function of the number ofbits (16 or 32 bit processors).

Its capabilities are a function of the number of bits (16 or 32bit processors). One byte contains a sufficient number of bits (8 bits = 1 byte)to represent any alphanumeric character in binary form.

1024 bytes = 1 kilobyte. 1 million bytes = 1 megabyte (1000 k). 1 billion bytes = 1 gigabyte (1000 mb).

Video/Image Displays

Larger number of pixels, the finer the detail. Also determined by radiometric resolution. Brightness value range - 1 bit = black & white; 6 bits = 64colors (minimum for b & w gray levels). Typically 8 bit = 256 brightness levels per R, G, B primaries.

EGA monitors - Enhanced Graphics M onitor, 640 x 350 pixelresolution w/ 0.42 mm dot pitch. VGA monitors - Video Graphics Array, 640 x 350 (64simultaneous colors ), 640 x 400, & 640 x 480 w/ 0.42 dotpitch. Multisynchronous monitor - 1024 x 768.

Establishing color Image display data held in a frame buffer, in a displayprocessor. Contains 1 or more bits to record BV per pixel. The greater the number of bits per pixel, the greater the rangeof brightness per pixel. Digital value is converted to an electrical signal by a digital toan analog converter.

Pseudocolor display (cheapest) Color/pixel stored in a look-up table. Number of colors determined by number of entries in thetable. Number of bits = number of colors/primary color, e.g. 8 bits= 0-255 BV's/R,G,B.

True/F ull Color

Separate memory/primary color each with its own look-uptable & D-to-A converter. Greater range of BV's/ table. M ay density or level slice a range of BV's and assign colorsto each range to enhance an image segment. 24 bit (8 bits per primary color) with 16,777,216 colors.