javascriptrrasterphotoshopextendscript

Stitch images and data from coupled microscopy/spectroscopy into panoramic in Photoshop or R

I have a set of images and X-ray data generated from coupled scanning electron microscopy and energy dispersive spectroscopy. Here's my problem:

I imaged transects of a rock surface like this (purple box outlines transect region):

enter image description here

I wanted really high resolution, so I did this using 7 images at 3000X magnification and stitched them together with the photomerge script in Photoshop. Here's an example of an individual image:

enter image description here

And its position in the photomerged image transect:

enter image description here

At each of these 7 locations, I also collected X-ray data that generates an element map for each element detected and writes this to a TIFF. I want to also stitch together each element map TIFF so I can overlay it on the merged transect image of the rock. This is the result I want:

enter image description here

The problem is that the element maps don't have enough features in them to be able to stitch them together with photomerge. It's basically binary - if an element is detected, the pixel is some color (like red for iron or yellow for sulfur in my example images), or black if the element is not detected. You can see there are large portions of the element maps that are mostly black.

I now have ~20 transects x 7 images each x ~10 elements which results in ~1400 images that need to be put together, hence the need for automation.

My idea was to stitch together the rock images with photomerge. The output of photomerge is a smart object where each image is a layer. Then, I would use a script to get the top left corner coordinates, the width, and height for each of the 7 images in the photomerged image object. I would then place and assign these properties to each of the corresponding element maps for the 7 images to generate the "merged" element maps to overlay on the image. I tried to work on this myself but I'm not proficient in javascript and couldn't wrap my head around the Photoshop API.

I uploaded an example dataset on Github here. The 7 transect positions are from left to right: -2, -1, 0, 1, 2, 3, 4. There are images of the rock and subdirectories with element data for each position.

Solution

  • It would have been nice to do this entirely in a Photoshop script or entirely in R, but I have a working solution that uses both. I manually pulled XY coords from the bottom left corner of each layer in the photomerge output from Photoshop and assigned them to rasterized images in R:

    #!/usr/bin/env Rscript

#Caitlin Casar
#github.com/caitlincasar
#19 March 2020
#DataStitchR stitches panoramic images of SEM images coupled to x-ray energy dispersive spectroscopy.

# usage: ./dataStitchR. -f "/Users/Caitlin/Desktop/dataStitcher/example_dataset" -b "/Users/Caitlin/Desktop/dataStitcher/example_dataset/SEM_images" -c "/Users/Caitlin/Desktop/dataStitcher/coordinates.txt" -z ".tif" -m ".tif" -a "Unknown|Os|SEM" -d "overview" -y "overview" -p TRUE -o "example" -n "example"
# usage Rscript dataStitchR.R -f "/Users/Caitlin/Desktop/dataStitcher/example_dataset" -b "/Users/Caitlin/Desktop/dataStitcher/example_dataset/SEM_images" -c "/Users/Caitlin/Desktop/dataStitcher/coordinates.txt" -z ".tif" -m ".tif" -a "Unknown|Os|SEM" -d "overview" -y "overview" -p TRUE -o "example" -n "example"

message("
                                        #####                                    ######  
        #####     ##    #####    ##    #     #  #####  #  #####   ####   #    #  #     # 
        #    #   #  #     #     #  #   #          #    #    #    #    #  #    #  #     # 
        #    #  #    #    #    #    #   #####     #    #    #    #       ######  ######  
        #    #  ######    #    ######        #    #    #    #    #       #    #  #   #   
        #    #  #    #    #    #    #  #     #    #    #    #    #    #  #    #  #    #  
        #####   #    #    #    #    #   #####     #    #    #     ####   #    #  #     # 
        

        ")

message("DataStitchR was created by Caitlin Casar and is maintained at github.com/CaitlinCasar/dataStitchR.
        ")
message("DataStitchR stitches panoramic images of SEM images coupled to x-ray energy dispersive spectroscopy.
        ")
message("For help, run 'dataStitchR.R --help'.
        
        
        ")

suppressPackageStartupMessages(require(optparse))

option_list = list(
  make_option(c("-f", "--file"), action="store", default=getwd(), type='character',
              help="Input parent directory with subdirectories of element xray data to be stitched. The element names should be abbreviated, i.e. 'Ca' for calcium."),
  make_option(c("-o", "--out"), action="store", default=NA, type='character',
              help="Output file directory. This is where your x-ray raster brick and output figures will be saved."),
  make_option(c("-n", "--name"), action="store", default=NA, type='character',
              help="Optional name for output files."),
  make_option(c("-b", "--base-images"), action="store", default=NA, type='character',
              help="SEM image file directory."),
  make_option(c("-c", "--coords"), action="store", default=NA, type='character',
              help="Tab-delimited file of xy coordinates for each image. A third column should denote stitching positions that correspond to the file names for each image."),
  make_option(c("-u", "--use-positions"), action="store", default="-?(?<![Kα1||Kα1_2])\\d+", type='character',
              help="Optional regex pattern to extract position IDs from each file name that corresponds to positions in the xy file. The default searches for numbers that appear after 'Kα1' or 'Kα2'. Numbers can include signs, i.e. -1 is acceptable."),
  make_option(c("-z", "--z-format"), action="store", default="*", type='character',
              help="Optional regex pattern of x-ray image formats to select for stitching, i.e. '.tif'."),
  make_option(c("-m", "--make"), action="store", default="*", type='character',
              help="Optional regex pattern of SEM image formats to select for stitching, i.e. '.tif'. You do not need to specify this unless you are generating a PDF output."),
  make_option(c("-a", "--all-exclude"), action="store", default=NA, type='character',
              help="Optional regex pattern of x-ray file directories to exclude from stitiching, i.e. the element your sample was coated with."),
  make_option(c("-d", "--drop"), action="store", default=NA, type='character',
              help="Optional regex pattern of files to exclude from x-ray data stitching."),
  make_option(c("-y", "--y-exclude"), action="store", default=NA, type='character',
              help="Optional regex pattern of files to exclude from SEM image stitiching. You do not need to specify this unless you are generating a PDF output."),
  make_option(c("-v", "--verbose"), action="store_true", default=TRUE,
              help="Print updates to console [default %default]."),
  make_option(c("-q", "--quiet"), action="store_false", dest="verbose",
              help="Do not print anything to the console."),
  make_option(c("-p", "--pdf"), action="store", default=FALSE,
              help="Generate PDF of x-ray brick colored by element superimposed on the SEM image, default is TRUE [default %default].")  
)
opt = parse_args(OptionParser(option_list=option_list))


#load dependencies 
suppressPackageStartupMessages(require(pacman))
pacman::p_load(raster, magick, tidyverse, rasterVis, ggnewscale, Hmisc, cowplot)

#create list all sub-directories within main directory
directories <- list.dirs(opt$f, full.names = T , recursive =F)
if(!is.na(opt$a)){
  directories <- directories[!str_detect(directories, opt$a)]
}


#set image coordinates
xy <- read_delim(opt$c, delim = "\t", col_types = cols())
positions <- xy %>%
  select(-x, -y)


# stitch xray images ------------------------------------------------------

#stitch xray images into panoramas and store in raster brick 
xray_brick_list <- list()
xray_data <- list()
for(j in 1:length(directories)){
  path = directories[j]
  files <- list.files(path, full.names = T, pattern = opt$z)
  if(!is.na(opt$d)){
    files <- files[!str_detect(files, opt$d)]
  }
  if(length(files) >0){
    xray_data[[j]] <- str_extract(path, "([^/]+$)")
    message(paste0("Stitching ", str_extract(xray_data[[j]], "([^/]+$)"), " data (element ", j, " of ", length(directories), ")..."))
    xy_id <- which(positions[[1]] %in% str_extract(files, opt$u))
    panorama <- list()
    for(i in 1:length(files)){
      message(paste0("Processing image ", i, " of ", length(files), "..."))
      image <- files[i] %>% image_read() %>% 
        image_quantize(colorspace = 'gray') %>% 
        image_equalize() 
      temp_file <- tempfile()
      image_write(image, path = temp_file, format = 'tiff')
      image <- raster(temp_file) %>%
        cut(breaks = c(-Inf, 150, Inf)) - 1
      image <- aggregate(image, fact=4)
      image_extent <- extent(matrix(c(xy$x[xy_id[i]], xy$x[xy_id[i]] + 1024, xy$y[xy_id[i]], xy$y[xy_id[i]]+704), nrow = 2, ncol = 2, byrow = T))
      image_raster <- setExtent(raster(nrows = 704, ncols = 1024), image_extent, keepres = F)
      values(image_raster) <- values(image)
      panorama[[xy_id[i]]] <- image_raster
    }
      empty_xy_id <- which(!positions[[1]] %in% str_extract(files, opt$u))
      if(length(empty_xy_id) > 0){
        for(k in 1:length(empty_xy_id)){
          empty_raster_extent <- extent(matrix(c(xy$x[empty_xy_id[k]], xy$x[empty_xy_id[k]] + 1024, xy$y[empty_xy_id[k]], xy$y[empty_xy_id[k]]+704), nrow = 2, ncol = 2, byrow = T))
          empty_raster <- setExtent(raster(nrows = 704, ncols = 1024), empty_raster_extent, keepres = F)
          values(empty_raster) <- 0
          panorama[[empty_xy_id[k]]] <- empty_raster
        }
      }
      panorama_merged <- do.call(merge, panorama)
      xray_brick_list[[j]] <- panorama_merged
  }
}

message("Stitching complete. Creating x-ray brick...")
xray_brick <- do.call(brick, xray_brick_list)
names(xray_brick) <- unlist(xray_data)
message("...complete.")

#write the brick 
message("Writing brick...")


if(!is.na(opt$o)){
  dir.create(opt$o)
  if(!is.na(opt$n)){
    out_brick <- writeRaster(xray_brick, paste0(opt$o, "/", opt$n,"_brick.grd"), overwrite=TRUE, format="raster")
    x <- writeRaster(xray_brick, paste0(opt$o, "/", opt$n,"_brick.tif"), overwrite=TRUE, format="GTiff",options=c("INTERLEAVE=BAND","COMPRESS=LZW"))
  }else{
    out_brick <- writeRaster(xray_brick, path = opt$o, "brick.grd", overwrite=TRUE, format="raster")
    x <- writeRaster(xray_brick, path = opt$o, "brick.tif", overwrite=TRUE, format="GTiff",options=c("INTERLEAVE=BAND","COMPRESS=LZW"))
  }
}else{
  if(!is.na(opt$n)){
    out_brick <- writeRaster(xray_brick, paste0(opt$n,"_brick.grd"), overwrite=TRUE, format="raster")
    x <- writeRaster(xray_brick, paste0(opt$n,"_brick.tif"), overwrite=TRUE, format="GTiff",options=c("INTERLEAVE=BAND","COMPRESS=LZW"))
  }else{
    out_brick <- writeRaster(xray_brick, "brick.grd", overwrite=TRUE, format="raster")
    x <- writeRaster(xray_brick, "brick.tif", overwrite=TRUE, format="GTiff",options=c("INTERLEAVE=BAND","COMPRESS=LZW"))
  }
}


message("...complete.")

#flush everything we don't need from memory
remove(list = c("x", "xray_brick_list", "xray_data", "empty_raster", "empty_raster_extent",
                "i", "j", "k", "path", "positions", "xy_id", 
                "panorama_merged", "panorama", "empty_xy_id", "files", "directories"))


# create base SEM image ---------------------------------------------------
if(opt$p){
  
if(!is.na(opt$b)){
  SEM_images <- list.files(opt$b, full.names = T, pattern = opt$m)
}else{
  message("Please provide a file path for your SEM images to stitch. For help, see 'dataStitchR.R --help.'")
  break
}

if(!is.na(opt$y)){
  SEM_images  <- SEM_images[!str_detect(SEM_images , opt$y)]
}
SEM_panorama <- list()

message("Stitching SEM images into panorama...")
for(i in 1:length(SEM_images)){
  image <- SEM_images[i] %>% image_read() %>%
    image_quantize(colorspace = 'gray') %>%
    image_equalize()
  temp_file <- tempfile()
  image_write(image, path = temp_file, format = 'tiff')
  image <- raster(temp_file)
  image_extent <- extent(matrix(c(xy$x[i], xy$x[i] + 1024, xy$y[i], xy$y[i]+704), nrow = 2, ncol = 2, byrow = T))
  image_raster <- setExtent(raster(nrows = 704, ncols = 1024), image_extent, keepres = F)
  values(image_raster) <- values(image)
  SEM_panorama[[i]] <- image_raster
}
SEM_panorama_merged <- do.call(merge, SEM_panorama)
message("...complete.")

#flush everything we don't need from memory
remove(list = c("SEM_panorama", "SEM_images", "image", "image_extent", "image_raster"))

#optinal plot to check if SEM image merge looks correct 
#plot(SEM_panorama_merged, col = gray.colors(10, start = 0.3, end = 0.9, gamma = 2.2, alpha = NULL))


# plot the data -----------------------------------------------------------

message("Generating plot...")
# Set color palette

#palette source: https://sciencenotes.org/molecule-atom-colors-cpk-colors/

element_colors <- c("#FFFFFF", "#D9FFFF", "#CC80FF", "#C2FF00", "#FFB5B5", "#909090", "#3050F8",
                    "#FF0D0D", "#90E050", "#B3E3F5", "#AB5CF2", "#8AFF00", "#BFA6A6", "#F0C8A0",
                    "#FF8000", "#FFFF30", "#1FF01F", "#80D1E3", "#8F40D4", "#3DFF00", "#E6E6E6",
                    "#BFC2C7", "#A6A6AB", "#8A99C7", "#9C7AC7", "#E06633", "#F090A0", "#50D050",
                    "#C88033", "#7D80B0", "#C28F8F", "#668F8F", "#BD80E3", "#FFA100", "#A62929",
                    "#5CB8D1", "#702EB0", "#00FF00", "#94FFFF", "#94E0E0", "#73C2C9", "#54B5B5",
                    "#3B9E9E", "#248F8F", "#0A7D8C", "#006985", "#C0C0C0", "#FFD98F", "#A67573",
                    "#668080", "#9E63B5", "#D47A00", "#940094", "#429EB0", "#57178F", "#00C900",
                    "#70D4FF", "#FFFFC7", "#D9FFC7", "#C7FFC7", "#A3FFC7", "#8FFFC7", "#61FFC7",
                    "#45FFC7", "#30FFC7", "#1FFFC7", "#00FF9C", "#00E675", "#00D452", "#00BF38",
                    "#00AB24", "#4DC2FF", "#4DA6FF", "#2194D6", "#267DAB", "#266696", "#175487",
                    "#D0D0E0", "#FFD123", "#B8B8D0", "#A6544D", "#575961", "#9E4FB5", "#AB5C00",
                    "#754F45", "#428296", "#420066", "#007D00", "#70ABFA", "#00BAFF", "#00A1FF",
                    "#008FFF", "#0080FF", "#006BFF", "#545CF2", "#785CE3", "#8A4FE3", "#A136D4",
                    "#B31FD4", "#B31FBA", "#B30DA6", "#BD0D87", "#C70066", "#CC0059", "#D1004F",
                    "#D90045", "#E00038", "#E6002E", "#EB0026")
names(element_colors) <- c("H",  "He", "Li", "Be", "B",  "C",  "N",  "O",  "F",  "Ne", "Na", "Mg", "Al", "Si",
                           "P",  "S",  "Cl", "Ar", "K",  "Ca", "Sc", "Ti", "V",  "Cr", "Mn", "Fe", "Co", "Ni",
                           "Cu", "Zn", "Ga", "Ge", "As", "Se", "Br", "Kr", "Rb", "Sr", "Y",  "Zr", "Nb", "Mo",
                           "Tc", "Ru", "Rh", "Pd", "Ag", "Cd", "In", "Sn", "Sb", "Te", "I",  "Xe", "Cs", "Ba",
                           "La", "Ce", "Pr", "Nd", "Pm", "Sm", "Eu", "Gd", "Tb", "Dy", "Ho", "Er", "Tm", "Yb",
                           "Lu", "Hf", "Ta", "W",  "Re", "Os", "Ir", "Pt", "Au", "Hg", "Tl", "Pb", "Bi", "Po",
                           "At", "Rn", "Fr", "Ra", "Ac", "Th", "Pa", "U",  "Np", "Pu", "Am", "Cm", "Bk", "Cf",
                           "Es", "Fm", "Md", "No", "Lr", "Rf", "Db", "Sg", "Bh", "Hs", "Mt")

xray_frame <- as.data.frame(xray_brick, xy=TRUE) 
xray_frame <- gather(xray_frame, element, value, colnames(xray_frame)[3]:colnames(xray_frame)[ncol(xray_frame)])



element_plotter<-function(coord_frame, brick, SEM_image, colors){
  p <-rasterVis::gplot(SEM_image) +
    geom_tile(aes(fill = value)) +
    scale_fill_gradient(low = 'black', high = 'white') +
    ggnewscale::new_scale_fill()
  for(i in names(brick)){ 
    message(paste0("Adding ", names(brick[[i]]), " to plot..."))
    element_coords <- coord_frame %>%
      filter(element == names(brick[[i]]) & value!=0)
    p <- p+geom_raster(element_coords, mapping = aes(x, y, fill = element, alpha = value)) +
      scale_fill_manual(values = colors) +
      ggnewscale::new_scale_fill()
  }
  message("Writing plot...")
  suppressWarnings(print(p + 
                           coord_fixed() +
                           theme(axis.title = element_blank(),
                                 axis.text = element_blank(),
                                 legend.position = "none")))
}

element_plot <- element_plotter(xray_frame, xray_brick, SEM_panorama_merged, element_colors)

element_plot_legend <- data.frame(element = unique(xray_frame$element)) %>%
  rownames_to_column() %>% 
  ggplot(aes(element, rowname, fill=element)) + 
  geom_bar(stat= "identity") + 
  scale_fill_manual(values = element_colors) +
  guides(fill=guide_legend(nrow=2)) +
  theme(legend.title = ggplot2::element_blank(),
        legend.text = ggplot2::element_text(size = 8))

element_plot_with_legend <- plot_grid(
  element_plot, 
  plot_grid(get_legend(element_plot_legend), 
            ncol = 1), 
  nrow = 2, 
  rel_heights = c(8,2)
)


# generate PDF ------------------------------------------------------------

if(!is.na(opt$n)){
  if(!is.na(opt$o)){
    pdf(paste0(opt$o, "/", opt$n, "_element_plot.pdf"),
        width = 13.33, 
        height = 7.5)
  }else{
    pdf(paste0(opt$n, "_element_plot.pdf"),
        width = 13.33, 
        height = 7.5)
  }
}else{
  if(!is.na(opt$o)){
    pdf(paste0(opt$o, "/", "element_plot.pdf"),
        width = 13.33, 
        height = 7.5)
  }else{
    pdf("element_plot.pdf",
        width = 13.33, 
        height = 7.5) 
  }
}


print(element_plot_with_legend)

dev.off()

message("...complete.")

remove(list = ls())

}