VCT 3080 Resample Lecture

400 views

Published on

VCT 3080 resample lecture

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
400
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
13
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

VCT 3080 Resample Lecture

  1. 1. Raster Images & Resizing two ways to resize a raster image. Change the pixel size (effective resolution) Change the number of pixels (resample)  There are only  
  2. 2. Raster Image  Photoshop™ can resample images. (change amount of pixels)  Resampling renders new pixels from old, by interpolating original pixel data.
  3. 3. Raster Image  Beware! All of the pixels are NEW.  They are not the same as the original capture.  “Artifacts” can be created by the resampling/rendering process.
  4. 4. Raster Image Resampling  Unwanted colors or effects may result from resampling
  5. 5. Raster Image (change the number of pixels)  Resampling  Upsampling  Add pixels to increase resolution  Downsampling  Delete pixels to decrease resolution  Change size of an image and maintain the original resolution
  6. 6. Raster Image Resampling  Downsampling  Good for reducing the file size of a large image  Upsampling can increase the resolution of an image with resampling.  Can reduce jagginess in CT images  Trade-off is image sharpness  It will not help BIG enlargements.
  7. 7. Raster Image Upsampling 72 ppi No Upsampling 72 ppi Upsampled to 72 ppi
  8. 8. - Line Art  It cannot make a jaggie bitmap image smooth!  Capture at a high resolution initially 100 PPI Line Art 200 PPI
  9. 9. Rasters & Rotation  Rotating a raster image results in a different pixel alignment caused by how the rotated image realigns to the image grid (raster).
  10. 10. Rasters & Rotation  Rotation triggers resampling.  Straight edges can become jagged.  Interpolation calculates the newly created pixels. Original Image Location Rotated Image New Pixel Location
  11. 11. Bit Depth Raster Image Characteristic 
  12. 12. Raster Image Bit Depth  The pixels will either represent black & white, shades of gray, or colors.  The data collected for each pixel is stored as bits of computer data.  A bit is the basic component of all computer data.
  13. 13. B&W - Grays  Black & white pixels are stored with one bit of data per pixel.  The bit is either a 0 OR a 1. 0 White Black
  14. 14. B&W - Grays  More than one bit is needed for storing shades of gray.  Two bits of data per pixel stores four shades of gray (black, dark gray, light gray, white).
  15. 15. B&W - Grays Original Photograph Grayscale Four Levels of Gray = 2 Bits of data per pixel
  16. 16. B&W - Grays  The number of bits per pixel as an exponent of 2 equals gray levels. 2 Number of bits 21 = 2 levels 22 = 4 levels 23 = 8 levels 24 = 16 level 28 = 256 levels Normal Grayscale Is 8 Bits/Pixel
  17. 17. Digital Values  With 8 bits, 256 different values (grays or colors) are possible.  We can count from 0 to 255.  0 = Black or no color or maximum color
  18. 18. Digital Color  Scanning red (R), green (G), and blue (B), a value is captured for each pixel.  Each R, G, and B value is captured and stored in 8 bits.  24 Bit = 16.7 million colors
  19. 19. Digital Color  Four Color Process is 32 bit Does NOT reproduce as 400 million colors
  20. 20. Digital Color  16 Bit Images - High-Bit  48 Bit Color (16 bits per color channel RGB)  Camera Raw .CRW  For editing only - Export at 24 Bit
  21. 21. Digital Color  Indexed Color  8 bit - 256 Colors (out of 16.7million)  Applied to GIF format  PNG-8  Supports indexed transparency 16 x 16 = 256 Color Index
  22. 22. File Compression  Large raster files often require compression  Two basic types of compression  Lossless - no data is lost in compression and extraction  LZW (TIFF, GIF)  ZIP  RLE (for line art)  "Lossy" - data is lost to achieve greater compression  JPEG – compress once

×