1. EE 638: Principles of Digital Color Imaging Systems Lecture 17: Digital Camera Characterization and Calibration

2. Image Capture Devices l Image Capture Devices: –Scanners –Camera l Camera: l Sensor array technologies –CCD (Charge Coupled Device) –CID (Charge Injection Device) –CMOS (Complementary Metal Oxide Semiconductor) Sensor Array CCD from a HP digital camera

3. l CCD –Phase I Exposure l CMOS & CID Line Registers y address x address 1 pixel Detector All detectors have a certain identical sensitivity

4. Camera (single chip) l Single chip –CCD –CMOS –CID l Sensor response –Coat cells with three different filter materials RGBRGB GBRGBR Corresponds to trichromatic sensor How do we get a full resolution array of RGB samples at each pixel?

5. Camera (single chip) l Single chip –CCD –CMOS –CID l Sensor response –Coat cells with three different filter materials RGBRGB GBRGBR Demosaic to get full resolution R, G, B Inverse problem Corresponds to trichromatic sensor

6. Camera (cont.) l Three chips l Foveon sensor R sensor G sensor B sensor Bean-splitter More expensive, but do get full resolution  no demosaicing, do have to worry about registration R G B incident light Layered Chip More expensive, but get full resolution  No registration issues but have cross-talk & efficiency issues

7. l Sensor Output l “Linear”  proportional to photon count similar to CRT monitor model. l Camera models exist that provide “raw” output. NL R NL G NL B Gamma correction A/D

8. l To determine nonlinearities, have to perform device characterization. l Set-up: illumination Target Target camera Colorimeter This is very similar to process used to determine nonlinearities for a scanner, except that scanner and X-Rite DTP 70 provide their own illumination, which can be more carefully controlled.

9. l To determine nonlinearities NL R, NL G, NL B, need a special facility of stimuli. (Target illuminant) l Let be the spectral stimulus of the i-th patch. l Want l then k— doesn’t depend on i l— doesn’t depend on i

10. l Caveat paper white Fraction of patch covered by colorant Fraction of patch not covered by colorant Sensor pixels Full colorant Rc Halftoned Target Kodak Q60 and Macbeth Color Checker targets are not printed, and therefore do not suffer from halftoning issues.

11. l Remainder of camera characterization requires finding T: –1) 2) NL R NL G NL B

12. l Normal approach for finding T is to measure large set of patches & perform linear regression. illumination Target Target camera Colorimeter NL Regression

13. Summary l 1) Typically can get < accuracy for displays (monitors) because we only need visual independence of primaries. l 2) For capture, have to have sensor response span HVS, i.e. there must exist a 3x3 matrix B such that l No.2 is much more restrictive than No.1 l  Above procedure will typically yield ~ (average error = ?)

14. l To do better, could use double exposure where illuminant is charged between exposures, or we place a filter over the lens for the second exposure. l This delves into an area sometimes known as Hi-Fi (High Fidelity) Color or Spectral Color. We will talk about this later in the course. l Another interesting and recently very popular topic related to camera characterization and calibration is high dynamic range (HDR) imaging. We may talk about this later in the semester.