Table Of Contents. v Copyright by Richard Berry and James Burnell, All Rights Reserved.

Transcription

1 Table Of Contents Preface to the First Edition... xix Preface to the Second Edition... xxv 1 Basic Imaging Light Image Formation Pinhole Imaging Lens Cameras Telescopes Detectors The Human Retina Photographic Emulsions Electronic Detectors Linearity, Saturation, and Blooming Sensor Geometry Aspect Ratio Pixel Count Image Capture Angular Field of View of a Detector Sampling the Image Angular Size of a Single Pixel Matching Pixels to the Point-Spread Function Counting Photons What Is a Signal? What Is Noise? Signals and Noise The Poisson and Gaussian Distributions Collecting More Photons by Image Summing Measuring Noise Signals Become More Complicated Unwanted Signals and More Sources of Noise Signals and Noise in Images Signal and Noise in a Raw Image Signal and Noise in a Dark Frame v Copyright by Richard Berry and James Burnell, All Rights Reserved.

2 2.4.3 Signal and Noise in a Dark-Subtracted Image The Effect of the Sky Background on Signal and Noise Signal and Noise in Multiple Averaged Images Signal and Noise Effects from Flat-Fielding A Little Sermon on Signals and Noise Digital Image Formats File Format Basics FITS: The Standard Format in Astronomy Overview of FITS The FITS Header Mandatory Keywords Array Value Keywords Observation Keywords Comment Keywords Header Value Formats The FITS Binary Data Array The FITS Tailer Nonconforming FITS Files Nonconforming Headers Nonconforming Data Arrays Uncoordinated FITS Headers and Data Arrays Reading Variant FITS Files TIFF: The Standard in the Graphic Arts BMP: Images for Windows AVI: Interleaved Audio/Video from Webcams JPEG: File Compression for the Internet RAW, NEF, and CRW: Proprietary Raw Images Imaging Tools Sensors and Optics Sensor Size and Field of View Pixel Size and Resolution Spectral Sensitivity Optics for Imaging Auxiliary Optics Reducing Focal Length Increasing Focal Length Correcting Field Curvature Correcting Coma Aberration Finding Celestial Objects Flip Mirrors, Finder Scopes, and Go-To Mounts Telescope Mountings Tracking Sensitivity Rate Errors and Periodic Errors Testing and Tuning a Clock Drive vi Handbook of Astronomical Image Processing

3 4.5.4 Periodic Error Correction (PEC) Drives Filters Filter Types Filters for H-Alpha and Other Emission Lines Light Pollution Rejection (LPR) Filters Blue-Block and Violet-Block Filters Recognizing and Correcting Equipment Problems Hot Spots Field Flooding Vignetting Dust Donuts Reaping the Benefits Imaging Techniques Accurate Polar Alignment Good Guiding Off-Axis Guiding Auxiliary Telescope Guiding Software Virtual Guiding Critical Focus The Focuser Focus Techniques Automated Focusing Correct Exposure Shooting Calibration Frames Basic, Standard, and Advanced Calibration Making Bias Frames Making Dark Frames Making Flat-Field Frames Defect Mapping Imaging with Digital SLR Cameras Deep-Sky Imaging Strategies for Deep-Sky Imaging Digital Snapshots Guided One-Shot Imaging Guided and Unguided Track-and-Stack Imaging Making Good Deep-Sky Images Imaging Deep-Sky Targets Lunar, Planetary, and Solar Imaging Techniques Obtaining Excellent Images Focal-Ratio Matching Optics Field of View Recording High-Resolution Images Making High-Resolution Images Solar System Targets Handbook of Astronomical Image Processing vii

4 5.9 The Role of Technique Image Calibration What s in a CCD Image? Photon Flux Nonuniformity Dark Current Zero-Point Bias Quantization Calibration is Peeling the Image Onion Calibration Frames Bias Frames Using a Single Bias Value Bias with Drift-Subtraction When to Make a Master Bias Frame Dark Frames Image-Times-Five Rule for Dark Frames Thermal Frames Standard and Scalable Dark Frames Dark Frame Matching Changing CCD Temperature When to Use a Single Dark Value Cosmic Ray Events Electroluminescence How to Make Master Dark Frames Flat Frames Four Types of Flat-Field Frames How to Shoot Light-Box and Dome Flats How to Shoot Twilight Flats How to Shoot Sky Flats Methods of Calibration Basic Image Calibration Standard Image Calibration Advanced Image Calibration The Calibrated Image Photons, Dark Current, and Readout Noise Noise from Calibration Image Stacking How to Spot Calibration Errors Bias Drift Changing CCD Temperature Changing Optical Configuration Defect Mapping and Correction Image Analysis Pixel Measurements viii Handbook of Astronomical Image Processing

5 7.1.1 Pixel Coordinates Pixel Value Whole-Image Analysis Image Statistics Minimum Pixel Value Maximum Pixel Value Mean Pixel Value Median Pixel Value Standard Deviation Low-Point and High-Point Pixel Values The Image Histogram Image Feature Analysis Pixel Statistics Defining a Region of Interest Minimum Pixel Value Maximum Pixel Value Mean Pixel Value Variance Standard Deviation Signal-to-Noise Ratio Median Pixel Value Mean of Median Half Determining a Centroid Distance on a CCD Image Image Profiles Astrometry Photometry Defining the Star Image Photometric Image Profile Spectroscopy Measuring CCD Performance Goals in CCD Testing Basic CCD Testing How to Make Basic CCD Test Images Basic Test Analysis Step 1: Mean and Standard Deviation in the Bias Step 2: Mean and Standard Deviation of the Flats Step 3: Measure the Dark Current Step 4: Compute the Conversion Factor Step 5: Compute the Readout Noise Step 6: Compute the Dark Current What Results to Expect Advanced CCD Testing Constructing a Low-Light Level Source Handbook of Astronomical Image Processing ix

6 8.3.2 Setting the Low-Level Light Source for Use How to Make Advanced CCD Test Images Make the Bias Frame Set Make the Skim Frame Set Make the Flat Frame Set Make the Dark Frame Set Analyzing the Advanced Test Image Set Check the Bias Frames for Noise and Interference Charge Skimming Check Plotting the Transfer Curve Checking the Linearity of the CCD Determining the Dark Current Check the Uniformity of the CCD Astrometry Astrometric Catalogs and Coordinates The Astrometric Dilemma Astrometric Catalogs and Reference Frames Astrometric Theory Standard Coordinates Plate Coordinates Improved Plate Constants Solving for Position Practical Astrometry CCD Images for Astrometry Scanned Photographs for Astrometry Making Astrometric Measurements Applied Astrometry Astrometry of Newly-Discovered Objects Astrometry of Asteroids and Comets Using Astrometry to Identify Objects Image Scale and Orientation Astrometry in Education Photometry Magnitudes: How Bright Is This Star? Magnitudes Are Comparisons Aperture Photometry Summing the Star s Light Subtracting Sky Background Raw Instrumental Magnitude Statistical Uncertainty Putting Photometry to Work Photometric Systems Atmospheric Extinction Transformation to the UBV(RI) System x Handbook of Astronomical Image Processing

7 10.4 Photometric Observing Preparing to Observe Differential Photometry All-Sky Photometry Do-What-You-Can Photometry Desiderata for Photometry Don t Be Afraid to Try! Spectroscopy What is Spectroscopy? Spectra and Spectrographs Prisms and Gratings Practical Spectrographs The Objective Prism Spectrograph The Grating-Prism Spectrograph The Slit Spectrograph The Fiber-Fed Spectrograph Properties of Spectrum Images Extracting a Spectrum from an Image Spectra from Objective Prism Images Spectra from Slit Spectrographs Spectra from Fiber-Fed Spectrographs Spectrum Calibration and Analysis Geometric Transforms Translation Rotation Scaling Practical Translation, Rotation, and Scaling Flipping and Flopping Cropping and Floating Resampling Point Operations Point Operations: An Overview Remapping Pixel Values Isolating the Range Transfer Functions Linear Transfer Function Gamma Transfer Function The Logarithmic Transfer Function The Gammalog Transfer Function The Negative Transfer Function The Sawtooth and Quantize Transfer Functions Direct Specification of the Transfer Function Direct Endpoint Specification Handbook of Astronomical Image Processing xi

8 Stretch Scaling Nonlinear Stretch Scaling Histogram Endpoint Specification Histogram Specification Histogram Equalization Gaussian Histogram Shaping Exponential Histogram Shaping Linear Operators Convolution in One Dimension One-Dimensional Examples Multiple Convolutions with One-Dimensional Kernels Convolution in Two Dimensions Convolution using Kernels Properties of the Convolution Kernel Kernels as Spatial Filters Smoothing Kernels (Low-Pass Filters) Sharpening Kernels (High-Pass Filters) Edge-Detection and Gradient Kernels Bas-Relief Operators Sobel, Kirsch, and Prewitt Operators Line-Detection Operators The Laplacian Operator Convolution by Unsharp Mask Generated Kernels for Unsharp Masking The Boxcar Unsharp Mask The Triangular Unsharp Mask The Gaussian Unsharp Mask The Power-Law Unsharp Mask Other Unsharp Masks Non-Linear Operators Rank Operators Minimum and Maximum The Median Operator The Rank-Order Operator The Multiplicative Rank Processes Non-Linear Enhancement Operators The Extreme Value Operator Local Adaptive Sharpening Noise Filters Morphological Operators Isophote Lines Frei and Chen Operators The Skeleton Operator Dilation, Erosion, Opening, and Closing Operators xii Handbook of Astronomical Image Processing

9 15.5 The Topographic Operator Digital Development Image Operations Image Math Addition Subtraction Multiplication Division Absolute Difference Merge Average Image Ranking Median Ranking Minimum Ranking Maximum Ranking Calibrating Images Dark Subtraction Flat-Fielding Basic Calibration Standard Calibration Advanced Calibration Image Registration Registration with Translation Only Registration with Translation, Rotation, and Scaling Blinking Images Track-and-Stack Image Summing and Averaging Images in Frequency Space Exploring Frequency Space Spatial Frequency The Frequency Spectrum Sinusoid Basics Fourier Theory Periodic Functions: The Fourier Series Nonperiodic Functions: The Fourier Integral Properties of the Fourier Transform Convolution via Fourier Transform Parseval s Theorem The Discrete Fourier Series The Fast Fourier Transform Image Processing using the Fourier Transform Butterworth Spatial Frequency Filters Feature Masking in Frequency Space Feature Enhancement in Frequency Space Handbook of Astronomical Image Processing xiii

10 18 Wavelets The Wavelet Transform The Wavelet Function Properties of the À Trous Wavelet Transform Spatial Filtering with the Wavelet Transform Spatial Filtering with Star Images Wavelet Noise Filters When Is an Image Feature Significant? Transforming Poisson Noise to a Gaussian Deviate Measuring Noise in Images Rejecting Noise and Retaining Significant Features The Solution: An Iterative Wavelet Noise Filter Wavelet K-Sigma Filtering Using Wavelets Deconvolution The Inverse Convolution Problem Image Estimation by Iteration Van Cittert Image Estimation Richardson-Lucy Image Estimation Using Deconvolution with Astronomical Images Building Color Images Human Color Vision The Trichromatic Basis of Color Vision Luminance and Chrominance Reproducing Color Celestial Light Starlight and Continuous Spectra Nebulae and Emission Spectra The Challenge of Celestial Color Imaging Red/Green/Blue Tri-Color Imaging Step 1: Capture Filtered Images Step 2: Correct the Filtered Images Subtract the Skylight Background Color Balance with G2V Stars Create the Color Image Summary: White-Balance Using G2V Stars Using Field Stars for White Balance Summary: White-Balance Using Field Stars Color Images from Filter-Matrix Cameras Color Space: Geometric Interpretations of Color RGB Color Space HSL Color Space Lab Color Space Luminance/RGB (LRGB) Color Imaging xiv Handbook of Astronomical Image Processing

11 Creating an Artificial Luminance Image Enhancing the Luminance Image Creating LRGB Images Practical RGB and LRGB Color Imaging Selecting Filters Shooting RGB and LRGB Images Trade-offs: RGB versus LRGB LLRGB (Multi-Luminance) Imaging Extended-Range and Narrowband Color Color Imaging with CMY Filters Selecting CMY Filters CMY versus RGB Imaging The Subjective Side of Color Images Processing Color Images Properties of Color Images Calibrate to Remove Dark Current and Vignetting Calibrating Bayer-Array Color Images Calibration for Digital Cameras Stacking to Enhance Signal-To-Noise Ratio Making Great Images with a Digital Camera Color Images in Color Spaces RGB Color Space HSL Color Space Lab Color Space Color in Color Images White Balance Luminance Enhancement of Color Images Appendix A Glossary Appendix B Resources B.1 CCD Imaging B.1.1 CCD Imaging Books B.2 Astronomical Optics B.2.1 Telescope Design B.2.2 Telescopes and Vision B.3 Astrometry B.3.1 Astrometry Books and Articles B.3.2 Astrometry Software B.3.3 Astrometry Reference Catalogs B.4 Photometry B.4.1 Photometry Books and Articles B.4.2 Photometric Data: Extinction Stars and Standard Stars B.4.3 Photometry Organizations B.4.4 Photometric Filters Handbook of Astronomical Image Processing xv

12 B.4.5 Photometry Software B.5 Spectroscopy B.5.1 Spectroscopy Books and Articles B.5.2 Spectroscopic Catalogs B.6 Image Processing B.6.1 Image Processing Books: General B.6.2 Image Processing: Science Applications B.6.3 Image Processing: Image Restoration B.6.4 Image Processing and the Fourier Transform B.6.5 Image Processing and Wavelets B.6.6 Image Processing Algorithms B.6.7 Image Processing Software B.7 Color Imaging B.7.1 Color Imaging Books Appendix C Tutorials C.1 Basic Skills C.2 Calibration C.3 Image Evaluation C.4 Astrometry C.5 Photometry C.5.1 Single-Star Photometry C.5.2 Single-Image Photometry C.5.3 Multiple-Image Photometry C.6 Spectroscopy C.7 Image Enhancement C.7.1 Brightness Scaling C.7.2 Histogram Shaping C.7.3 Convolution Filtering C.7.4 Unsharp Masking C.7.5 Deconvolution C.7.6 Wavelet Spatial Filtering C.7.7 Morphological Processing C.8 Fast Fourier Transform C.9 Multiple Image Processing C.9.1 Track and Stack C.9.2 Multi-Image Processing C.9.3 Multi-Image Alignment C.10 Image Registration and Blinking C.11 Deep-Sky Images C.12 Planetary Images C.13 Color Images C.14 Conclusion Index xvi Handbook of Astronomical Image Processing