Tytus Bernas Biological applications of image processing.

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Presentation transcript:

Tytus Bernas Biological applications of image processing

JC Russ (1998) Image processing handbook Image acquisition system

JC Russ (1998) Image processing handbook Digitization…

Coordinate system of digital image (square pixels)... and its effects

Pixels T

Advantage of (mega)pixels

Microscope resolution

d ~ R Airy d = λ /NA d ~ JDD d = λ /NA d ~ FWHM d = λ /NA Microscope resolution

frequency 1x 2x 3x Nyquist criterion theoretical: 2x practical: 3x Perfect sampling

Fourier transform PSF MTF

Modulation transfer function (MTF)

Widefield: Δx = λ em / (4 n sin α) Δz = λ em / (2 n (1- cos α)) Confocal: Δx = λ ex / (8 n sin α) Δz = λ ex / (4 n (1- cos α)) PSF MTF Perfect sampling

Aliasing

E.H.K. Stelzer et al. (1998) J. Microscopy 189 p PSF/MTF and noise

JC Russ (1998) Image processing handbook Camera: an array detector

Charge Coupled Device JC Russ (1998) Image processing handbook, CCD readout

NOISE ! readout dark quantum blooming SNR = PQ e t / [PQ e t + Dt + Nr 2 ] 1/2 linearity Problems of (digital) cameramen

Quantization accuracy gain & ofset binning (pixel size) acquisition time Qantization, detector settings

low offset high offsethigh gain low gain Gain and offset

Image is a two-dimensional function of coordinates: I=f(x,y) Minimum: 0 (or 1) Maximum: dynamic range Computer image = table of numbers

Dynamic range

1, 2, 3, 4, 5, 6, 7, 8, 9...er aha! 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 20, , , and so on      10 1   1 4  802308023 1412214122 0202102021 1112011120 1  16 1  = 21 Binary notation

product (AND) pq r sum (OR) pq r negation (NOT) p r AND OR NOT ABA AND B A OR BA exOR BNOT A Logic

Segmentation with binary mask I > t => 1 I 1 binarization log. AND

Mapping function (LUT)

image dark <> bright contrast low <> high Whole image: histogram

"What is truth?" Pontius Pilate (John 18:38) Conversion

Image improvement – convolution (averaging) x3 (1) 3x3 (3) 7x7 (1) x3 pix. 7x7 pix.

Better than average - median x3 median 3x3 gauss.

Enhancement of details - convolution x3 laplacian 3x3 derivative 9 3x3 hi-pass

Additive space: Red Green Blue Subtractive space : Cyan Magenta Yellow Hue Saturation Brigtthess Lightness a b Colour spaces

Warm and cold colours

Colour components I

Colour components II

(Pseudo)colours

Where to store it File typeBit depthColor coding Transp. (bits) compressionPortabilityRemarks losslesslossy BMP1/4/8grayscale ---- RLE ---- Poor (Microsoft format) Inefficient compression 1 24RGB- GIF8RGB color table1LZW-ExcellentNo grayscale support. JPEG24YUV--JPEGGood Very efficient compression 1 (with distorion). No RGB and grayscale support. JPEG20001/4/8color table38 2 JPEG200 fair Very efficient compression 1. Relatively new format intended to replace jpeg. 8/16grayscale 24/48RGB 36/64CMYK PNG1/2/4/8 grayscale or RGB color table 8deflation-good Efficient compression The format developed to replace GIF in www. 24/48RGB TIFF1/4/8RGB color table8 Deflation (ZIP), RLE, Huffman, LZW JPEGgood Format offers large array of features, which may be extended further using specific tags. Only limited number of these is supported universally, though. Efficient compression 1. 1/4/8/16grayscale 24/48RGB, YUV 32/64CMYK