fast performance when reading multiple *.gif images

Question

My computer (i5-6500 3.2 GHZ, 8 GB RAM) takes a long time: something like 10 minutes (havent yet measured exactly).

i currently have to

1. read 400 images. (*.gif format, should all be b&w, resolution of approx. 200*400 px.) (3520 images in total)

2. i want to "add" all images "cell-wise".

here is how im doing it at the moment: Read image with raster than turn it into matrix, then sum it.

library(rgdal)
library(raster)
library(magrittr)

oldPic <- raster("initalImage.gif") %>% as.matrix

for (pat_IND in currSide) {
    newPic <- raster(pat_IND) %>% as.matrix
    oldPic <- oldPic + newPic
}

This takes for ever. I used caTools::read.gif() which was even much slower. Do i have a bottle neck in my code? Is there a faster implementation?

Edit: Image Properties

i use "no dither", mono palette (b&w).

Edit2

i want to add the images pixel-wise. Lets take pic A and pic B.

A + B = C. If A(1,1) = 1 and B(1,1) = 1, C(1,1) should be 2. Its a simple matrix addition.

test image:

1. reading with raster takes 0.03699994 secs
2. reading with raster + as.matrix takes: 0.201 secs

Answer 1

you need to measure... without any sample image is hard to say and we can only guess. You need to take into account that loading/decoding JPG take time in milliseconds and encoding of GIF can be time consuming even 200 ms. Depends on kind of encoding. To speed up GIF encoding you can:

1. use single global palette + dithering

   GIF is 8 bpp and JPG is 24 bpp so your encoder needs to do the transformation. That is called color quantization and is the most expensive operation while encoding which can take even ~200 ms per frame on average PC machine in well optimized C++ code. for more info see:

   • Effective gif/image color quantization?

   To remedy this you can use single palette dedicated to dithering (like default VGA or use some WEB palette they have the same purpose) and use dithering with is much much faster. See:

   • simple and fast Dithering

   btw if you need to preserve colors take a look at this:

   • Images lose quality after saving as GIF

   So try to find out how to configure your encoder to force dithering instead of color quantization based on K-means or similar ....

2. limit encoding dictionary to less then 4096

   The encoding/decoding is based on creating dictionary and encoding need to search it more than once on per pixel basis. So lovering its size to 1024 gets significant boost to speed. Of coarse you need to access to encoding code to change this unless this can be configured somehow in it... The compression will be decreased by this however and more clear codes will be present in the stream.

3. use multi-threading

   you can fully parallelize this and encode with each core present in your system.

I strongly recommend you to measure how long it take to encode single frame of GIF. If you take advantage on both bullets #1,#2 then I estimate you can get near times around ~5 ms per frame with dithering and ~60 ms per frame with fast quantization. So with 3520 frames it would take around 17.6 or 211.2 seconds just to encode GIF so add the file memory and JPG manipulation and take into account all is heavily guessed/estimated as you did not provide sample data. And divide by number of cores if you use #3 +/- shared disc access waits.