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authorJörg Frings-Fürst <debian@jff-webhosting.net>2015-10-08 12:32:49 +0200
committerJörg Frings-Fürst <debian@jff-webhosting.net>2015-10-08 12:32:49 +0200
commitcfd27ef2ad8b005fd47ab41ef29b71d9e3d48201 (patch)
tree56cb8849a5df91b19b72fd4f48c79c343cd9bc5e /include/sane/sanei_ir.h
parentba8d09abe681600aad991f4a75e904615b7ed29f (diff)
Imported Upstream version 1.0.25upstream/1.0.25
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+/** @file sanei_ir.h
+ *
+ * This file provides an interface to the
+ * sanei_ir functions for utilizing the infrared plane
+ *
+ * Copyright (C) 2012 Michael Rickmann <mrickma@gwdg.de>
+ *
+ * This file is part of the SANE package.
+ *
+ * Essentially three things have to be done:
+ * - 1) reduce red spectral overlap from the infrared (ired) plane
+ * - 2) find the dirt
+ * - 3) replace the dirt
+ *
+ * - 1) is mainly adressed by sanei_ir_spectral_clean
+ * - 2) by sanei_ir_filter_madmean
+ * - 3) by sanei_ir_dilate_mean
+ */
+
+
+#ifndef SANEI_IR_H
+#define SANEI_IR_H
+
+#include <stdint.h>
+
+#define SAMPLE_SIZE 40000 /**< maximal for random sampling */
+
+#define HISTOGRAM_SHIFT 8 /**< standard histogram size */
+#define HISTOGRAM_SIZE (1 << HISTOGRAM_SHIFT)
+
+#define SAFE_LOG(x) ( ((x) > 0.0) ? log ((x)) : (0.0) ) /**< define log (0) = 0 */
+
+#define MAD_WIN2_SIZE(x) ( (((x) * 4) / 3) | 1 ) /**< MAD filter: 2nd window size */
+
+typedef uint16_t SANE_Uint;
+
+/**
+ * @brief Pointer to access values of different bit depths
+ */
+typedef union
+{
+ uint8_t *b8; /**< <= 8 bits */
+ uint16_t *b16; /**< > 8, <= 16 bits */
+}
+SANEI_IR_bufptr;
+
+
+/** Initialize sanei_ir.
+ *
+ * Call this before any other sanei_ir function.
+ */
+extern void sanei_ir_init (void);
+
+/**
+ * @brief Create the normalized histogram of a grayscale image
+ *
+ * @param[in] params describes image
+ * @param[in] img_data image pointer { grayscale }
+ * @param[out] histogram an array of double with histogram
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * @note
+ * histogram has to be freed by calling routine
+ */
+extern SANE_Status
+sanei_ir_create_norm_histogram (const SANE_Parameters * params,
+ const SANE_Uint *img_data,
+ double ** histogram);
+
+/**
+ * @brief Implements Yen's thresholding method
+ *
+ * @param[in] params describes image
+ * @param[in] norm_histo points to a normalized histogram
+ * @param[out] thresh found threshold
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * -# Yen J.C., Chang F.J., and Chang S. (1995) "A New Criterion
+ * for Automatic Multilevel Thresholding" IEEE Trans. on Image
+ * Processing, 4(3): 370-378
+ * -# Sezgin M. and Sankur B. (2004) "Survey over Image Thresholding
+ * Techniques and Quantitative Performance Evaluation" Journal of
+ * Electronic Imaging, 13(1): 146-165
+ * -# M. Emre Celebi, 06.15.2007, fourier_0.8,
+ * http://sourceforge.net/projects/fourier-ipal/
+ * -# ImageJ Multithresholder plugin,
+ * http://rsbweb.nih.gov/ij/plugins/download/AutoThresholder.java
+ */
+extern SANE_Status
+sanei_ir_threshold_yen (const SANE_Parameters * params,
+ double * norm_histo, int *thresh);
+
+/**
+ * @brief Implements Otsu's thresholding method
+ *
+ * @param[in] params describes image
+ * @param[in] norm_histo points to a normalized histogram
+ * @param[out] thresh found threshold
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * -# Otsu N. (1979) "A Threshold Selection Method from Gray Level Histograms"
+ * IEEE Trans. on Systems, Man and Cybernetics, 9(1): 62-66
+ * -# M. Emre Celebi, 06.15.2007, fourier_0.8
+ * http://sourceforge.net/projects/fourier-ipal/
+ */
+extern SANE_Status
+sanei_ir_threshold_otsu (const SANE_Parameters * params,
+ double * norm_histo, int *thresh);
+
+/**
+ * @brief Implements a Maximum Entropy thresholding method
+ *
+ * @param[in] params describes image
+ * @param[in] norm_histo points to a normalized histogram
+ * @param[out] thresh found threshold
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * -# Kapur J.N., Sahoo P.K., and Wong A.K.C. (1985) "A New Method for
+ * Gray-Level Picture Thresholding Using the Entropy of the Histogram"
+ * Graphical Models and Image Processing, 29(3): 273-285
+ * -# M. Emre Celebi, 06.15.2007, fourier_0.8
+ * http://sourceforge.net/projects/fourier-ipal/
+ * -# ImageJ Multithresholder plugin,
+ * http://rsbweb.nih.gov/ij/plugins/download/AutoThresholder.java
+ */
+extern SANE_Status
+sanei_ir_threshold_maxentropy (const SANE_Parameters * params,
+ double * norm_histo, int *thresh);
+
+/**
+ * @brief Generate gray scale luminance image from separate R, G, B images
+ *
+ * @param params points to image description
+ * @param[in] in_img pointer to at least 3 planes of image data
+ * @param[out] out_img newly allocated image
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ * - SANE_STATUS_UNSUPPORTED - wrong input bit depth
+ *
+ * @note out_img has to be freed by the calling routine.
+ * @note on input params describe a single color plane,
+ * on output params are updated if image depth is scaled
+ */
+SANE_Status
+sanei_ir_RGB_luminance (SANE_Parameters * params, const SANE_Uint **in_img,
+ SANE_Uint **out_img);
+
+/**
+ * @brief Convert image from >8 bit depth to an 8 bit image.
+ *
+ * @param[in] params pimage description
+ * @param[in] in_img points to input image data
+ * @param[out] out_params if != NULL
+ * receives description of new image
+ * @param[out] out_img newly allocated 8-bit image
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ * - SANE_STATUS_UNSUPPORTED - wrong input bit depth
+ *
+ * @note
+ * out_img has to be freed by the calling routine,
+ */
+
+extern SANE_Status
+sanei_ir_to_8bit (SANE_Parameters * params, const SANE_Uint *in_img,
+ SANE_Parameters * out_params, SANE_Uint **out_img);
+
+/**
+ * @brief Allocate and initialize logarithmic lookup table
+ *
+ * @param[in] length of table, usually 1 << depth
+ * @param[out] lut_ln adress of pointer to allocated table
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * @note natural logarithms are provided
+ */
+SANE_Status sanei_ir_ln_table (int len, double **lut_ln);
+
+/**
+ * @brief Reduces red spectral overlap from an infrared image plane
+ *
+ * @param[in] params pointer to image description
+ * @param[in] lut_ln pointer lookup table
+ * if NULL it is dynamically handled
+ * @param[in] red_data pointer to red image plane
+ * @param ired_data pointer to ired image plane
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * This routine is based on the observation that the relation beween the infrared value
+ * ired and the red value red of an image point can be described by ired = b + a * ln (red).
+ * First points are randomly sampled to calculate the linear regression coefficent a.
+ * Then ired' = ired - a * ln (red) is calculated for each pixel. Finally, the ir' image
+ * is scaled between 0 and maximal value. For the logarithms a lookup table is used.
+ * Negative films show very little spectral overlap but positive film usually has to be
+ * cleaned. As we do a statistical measure of the film here dark margins and lumps of
+ * dirt have to be excluded.
+ *
+ * @note original ired data are replaced by the cleaned ones
+*/
+extern SANE_Status
+sanei_ir_spectral_clean (const SANE_Parameters * params, double *lut_ln,
+ const SANE_Uint *red_data,
+ SANE_Uint *ir_data);
+
+/**
+ * @brief Optimized mean filter
+ *
+ * @param[in] params pointer to image description
+ * @param[in] in_img Pointer to grey scale image data
+ * @param[out] out_img Pointer to grey scale image data
+ * @param[in] win_rows Height of filtering window, odd
+ * @param[in] win_cols Width of filtering window, odd
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ * - SANE_STATUS_INVAL - wrong window size
+ *
+ * @note At the image margins the size of the filtering window
+ * is adapted. So there is no need to pad the image.
+ * @note Memory for the output image has to be allocated before
+ */
+extern SANE_Status
+sanei_ir_filter_mean (const SANE_Parameters * params,
+ const SANE_Uint *in_img, SANE_Uint *out_img,
+ int win_rows, int win_cols);
+
+
+/**
+ * @brief Find noise by adaptive thresholding
+ *
+ * @param[in] params pointer to image description
+ * @param[in] in_img pointer to grey scale image
+ * @param[out] out_img address of pointer to newly allocated binary image
+ * @param[in] win_size Size of filtering window
+ * @param[in] a_val Parameter, below is definetly clean
+ * @param[in] b_val Parameter, above is definetly noisy
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * This routine follows the concept of Crnojevic's MAD (median of the absolute deviations
+ * from the median) filter. The first median filter step is replaced with a mean filter.
+ * The dirty pixels which we wish to remove are always darker than the real signal. But
+ * at high resolutions the scanner may generate some noise and the ired cleaning step can
+ * reverse things. So a maximum filter will not do.
+ * The second median is replaced by a mean filter to reduce computation time. Inspite of
+ * these changes Crnojevic's recommendations for the choice of the parameters "a" and "b"
+ * are still valid when scaled to the color depth.
+ *
+ * @reco Crnojevic recommends 10 < a_val < 30 and 50 < b_val < 100 for 8 bit color depth
+ *
+ * @note a_val, b_val are scaled by the routine according to bit depth
+ * @note "0" in the mask output is regarded "dirty", 255 "clean"
+ *
+ * -# Crnojevic V. (2005) "Impulse Noise Filter with Adaptive Mad-Based Threshold"
+ * Proc. of the IEEE Int. Conf. on Image Processing, 3: 337-340
+ */
+extern SANE_Status
+sanei_ir_filter_madmean (const SANE_Parameters * params,
+ const SANE_Uint *in_img,
+ SANE_Uint ** out_img, int win_size,
+ int a_val, int b_val);
+
+
+/**
+ * @brief Add dark pixels to mask from static threshold
+ *
+ * @param[in] params pointer to image description
+ * @param[in] in_img pointer to grey scale image
+ * @param mask_img pointer to binary image (0, 255)
+ * @param[in] threshold below which the pixel is set 0
+ */
+void
+sanei_ir_add_threshold (const SANE_Parameters * params,
+ const SANE_Uint *in_img,
+ SANE_Uint * mask_img, int threshold);
+
+
+/**
+ * @brief Calculates minimal Manhattan distances for an image mask
+ *
+ * @param[in] params pointer to image description
+ * @param[in] mask_img pointer to binary image (0, 255)
+ * @param[out] dist_map integer pointer to map of closest distances
+ * @param[out] idx_map integer pointer to indices of closest pixels
+ * @param[in] erode == 0: closest pixel has value 0, != 0: is 255
+ *
+ * manhattan_dist takes a mask image consisting of 0 or 255 values. Given that
+ * a 0 represents a dirty pixel and erode != 0, manhattan_dist will calculate the
+ * shortest distance to a clean (255) pixel and record which pixel that was so
+ * that the clean parts of the image can be dilated into the dirty ones. Thresholding
+ * can be done on the distance. Conversely, if erode == 0 the distance of a clean
+ * pixel to the closest dirty one is calculated which can be used to dilate the mask.
+ *
+ * @ref extended and C version of
+ * http://ostermiller.org/dilate_and_erode.html
+ */
+void
+sanei_ir_manhattan_dist (const SANE_Parameters * params,
+ const SANE_Uint * mask_img, unsigned int *dist_map,
+ unsigned int *idx_map, unsigned int erode);
+
+
+/**
+ * @brief Dilate or erode a mask image
+ *
+ * @param[in] params pointer to image description
+ * @param mask_img pointer to binary image (0, 255)
+ * @param dist_map integer pointer to map of closest distances
+ * @param idx_map integer pointer to indices of closest pixels
+ * @param[in] by number of pixels, > 0 dilate, < 0 erode
+ *
+ * @note by > 0 will enlarge the 0 valued area
+ */
+void
+sanei_ir_dilate (const SANE_Parameters * params, SANE_Uint * mask_img,
+ unsigned int *dist_map, unsigned int *idx_map, int by);
+
+/**
+ * @brief Suggest cropping for dark margins of positive film
+ *
+ * @param[in] params pointer to image description
+ * @param[in] dist_map integer pointer to map of closest distances
+ * @param[in] inner crop within (!=0) or outside (==0) the image's edges
+ * @param[out] edges pointer to array holding top, bottom, left
+ * and right edges
+ *
+ * The distance map as calculated by sanei_ir_manhattan_dist contains
+ * distances to the next clean pixel. Dark margins are detected as dirt.
+ * So the first/last rows/columns tell us how to crop. This is rather
+ * fast if the distance map has been calculated anyhow.
+ */
+void
+sanei_ir_find_crop (const SANE_Parameters * params,
+ unsigned int * dist_map, int inner, int * edges);
+
+/**
+ * @brief Dilate clean image parts into dirty ones and smooth int inner,
+ *
+ * @param[in] params pointer to image description
+ * @param in_img array of pointers to color planes of image
+ * @param[in] mask_img pointer to dirt mask image
+ * @param[in] dist_max threshold up to which dilation is done
+ * @param[in] expand the dirt mask before replacing the pixels
+ * @param[in] win_size size of adaptive mean filtering window
+ * @param[in] smooth triangular filter whole image for grain removal
+ * @param[in] inner find crop within or outside the image's edges
+ * @param[out] crop array of 4 integers, if non-NULL, top, bottom,
+ * left and right values for cropping are returned.
+ *
+ * @return
+ * - SANE_STATUS_GOOD - success
+ * - SANE_STATUS_NO_MEM - if out of memory
+ *
+ * The main purpose of this routine is to replace dirty pixels.
+ * As spin-off it obtains half of what is needed for film grain
+ * smoothening and most of how to crop positive film.
+ * To speed things up these functions are also implemented.
+ */
+SANE_Status
+sanei_ir_dilate_mean (const SANE_Parameters * params,
+ SANE_Uint **in_img,
+ SANE_Uint *mask_img,
+ int dist_max, int expand, int win_size,
+ SANE_Bool smooth, int inner,
+ int *crop);
+
+
+#endif /* not SANEI_IR_H */