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Introduction to Digital Image Analysis Part I: Digital Images
Kurt Thorn NIC UCSF Image: Susanne Rafelski, Marshall lab
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Many measurements of light intensity
What is a digital Image? Many measurements of light intensity 1 3 5 4 2 6 13 20 11 14 44 75 81 45 12 28 98 255 234 78 27 94 215 194 68 18 39 66 63 35 8
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Bit depth and dynamic range
# of bits range 1 2 2 4 4 16 8 256 1-byte 12 4096 2-bytes 16 65536
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Bit depth and dynamic range
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Your monitor is an 8-bit display
Converting bit-depth Your monitor is an 8-bit display # of bits range 1 2 2 4 4 16 8 256 12 4096 16 65536
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Mapping values onto display
255 255 Display Intensity Digital Number
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Intensity scaling Computer screens are 8-bit
Publishers also want 8-bit files 255 Final Intensity 4095 Original Intensity You lose information in this process – values all end up as 255
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Intensity scaling Max 255 Contrast Final Intensity Brightness 4095
4095 Original Intensity Min
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Brightness / Contrast adjustment
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Be aware of how your software scales your image
Brightness/contrast Be aware of how your software scales your image Auto-Scale Full Range
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Be aware of how your software scales your image
Brightness/contrast Be aware of how your software scales your image High B/C Full Range
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Gamma correction Other contrast stretching transforms…. g=0.45
Output Intensity g=2.2 g=1 Input Intensity Other contrast stretching transforms….
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Gamma adjustment g=0.6 g=1 0.6 g=2.2
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What are acceptable image manipulations?
JCB has the best guidelines Brightness and contrast adjustments ok, so long as done over whole image and don’t obscure or eliminate background Nonlinear adjustments (like gamma) must be disclosed No cutting and pasting of regions within an image (e.g. individual cells) Control and experiment must be treated identically
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Lookup Tables (LUTs) 1 3
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False coloring to bring out detail
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False coloring to bring out detail
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Lookup Tables (LUTs)
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Lookup Tables (LUTs)
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Color Images Color images are made up of three gray scale images, one for each of red, green, and blue Can be 8 or 16 bits per channel
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Color Images
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Color Images 0 0 0 = Or 255 93 134 214 137 249 209 89 255 90 39 185 139 93 231 185 255
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Stacks: Sequences of images
Can represent time series(movies), z-positions, or other variables 813 790 827 860 873 771 807 882 921 1216 1062 940 815 962 1816 3422 2185 1140 803 1094 2395 3816 4134 1244 784 892 1464 1961 1689 1139 820 884 965 1082 1146 990 760 763 801 767 817 745 723 766 795 864 867 860 703 800 1016 1574 1299 849 744 829 1146 11117 2378 1030 756 792 908 1337 1149 883 757 874 880 823 831 651 790 915 1115 1086 871 799 1036 1851 2689 2300 1306 917 1688 2626 2354 2081 2304 983 2071 1790 4394 3187 2634 825 1671 2542 1820 1799 2206 803 1092 1823 2183 2314 1430 Z
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File Formats Data sets can be big: 1392 × 1040 × 2 = 2.8MB
3-channels, 15 image z-stack, 200 time points: 2.8 × 3 × 15 × 200 = 25.2GB Compression!
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Compression Lossless vs. Lossy
Lossless: preserves all information in original image Original image can be restored Lossy: discards information not necessary for visual appearance Original image cannot be restored See:
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File Formats Most portable: TIFF
8 or 16-bit, lossless, supports grayscale or RGB Good: JPEG2000, custom formats (nd2, ids, zvi, lsm, etc.) Lossless, supports full bitdepth Custom formats often support multidimensional images Not so portable Generally Bad: Jpeg, GIF, BMP, etc. Lossy and / or 8-bit
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Software Tools Photoshop Gimp NIS-Elements AxioVision MetaMorph Zen
Acquisition + Analysis Presentation Photoshop Gimp NIS-Elements AxioVision MetaMorph Zen Slidebook Micro-Manager Analysis Matlab ImageJ Imaris (3D visualization) CellProfiler
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Acknowledgements Nico Stuurman
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