Appending to an Image File

Question

I have written a program that takes a 'photo' and for every pixel it chooses to insert an image from a range of other photos. The image chosen is the photo of which the average colour is closest to the original pixel from the photograph.

I have done this by firstly averaging the rgb values from every pixel in 'stock' image and then converting it to CIE LAB so i could calculate the how 'close' it is to the pixel in question in terms of human perception of the colour.

I have then compiled an image where each pixel in the original 'photo' image has been replaced with the 'closest' stock image.

It works nicely and the effect is good however the stock image size is 300 by 300 pixels and even with the virtual machine flags of "-Xms2048m -Xmx2048m", which yes I know is ridiculus, on 555px by 540px image I can only replace the stock images scaled down to 50 px before I get an out of memory error.

So basically I am trying to think of solutions. Firstly I think the image effect itself may be improved by averaging every 4 pixels (2x2 square) of the original image into a single pixel and then replacing this pixel with the image, as this way the small photos will be more visible in the individual print. This should also allow me to draw the stock images at a greater size. Does anyone have any experience in this sort of image manipulation? If so what tricks have you discovered to produce a nice image.

Ultimately I think the way to reduce the memory errors would be to repeatedly save the image to disk and append the next line of images to the file whilst continually removing the old set of rendered images from memory. How can this be done? Is it similar to appending a normal file.

Any help in this last matter would be greatly appreciated.

Thanks,

Alex

Answer 1

I suggest looking into the Java Advanced Imaging (JAI) API. You're probably using BufferedImage right now, which does keep everything in memory: source images as well as output images. This is known as "immediate mode" processing. When you call a method to resize the image, it happens immediately. As a result, you're still keeping the stock images in memory.

With JAI, there are two benefits you can take advantage of.

1. Deferred mode processing.
2. Tile computation.

Deferred mode means that the output images are not computed right when you call methods on the images. Instead, a call to resize an image creates a small "operator" object that can do the resizing later. This lets you construct chains, trees, or pipelines of operations. So, your work would build a tree of operations like "crop, resize, composite" for each stock image. The nice part is that the operations are just command objects so you aren't consuming all the memory while you build up your commands.

This API is pull-based. It defers computation until some output action pulls pixels from the operators. This quickly helps save time and memory by avoiding needless pixel operations.

For example, suppose you need an output image that is 2048 x 2048 pixels, scaled up from a 512x512 crop out of a source image that's 1600x512 pixels. Obviously, it doesn't make sense to scale up the entire 1600x512 source image, just to throw away 2/3 of the pixels. Instead, the scaling operator will have a "region of interest" (ROI) based on it's output dimensions. The scaling operator projects the ROI onto the source image and only computes those pixels.

The commands must eventually get evaluated. This happens in a few situations, mostly relating to output of the final image. So, asking for a BufferedImage to display the output on the screen will force all the commands to evaluate. Similarly, writing the output image to disk will force evaluation.

In some cases, you can keep the second benefit of JAI, which is tile based rendering. Whereas BufferedImage does all its work right away, across all pixels, tile rendering just operates on rectangular sections of the image at a time.

Using the example from before, the 2048x2048 output image will get broken into tiles. Suppose these are 256x256, then the entire image gets broken into 64 tiles. The JAI operator objects know how to work a tile at a tile. So, scaling the 512x512 section of the source image really happens 64 times on 64x64 source pixels at a time.

Computing a tile at a time means looping across the tiles, which would seem to take more time. However, two things work in your favor when doing tile computation. First, tiles can be evaluated on multiple threads concurrently. Second, the transient memory usage is much, much lower than immediate mode computation.

All of which is a long-winded explanation for why you want to use JAI for this type of image processing.

---

A couple of notes and caveats:

1. You can defeat tile based rendering without realizing it. Anywhere you've got a BufferedImage in the workstream, it cannot act as a tile source or sink.
2. If you render to disk using the JAI or JAI Image I/O operators for JPEG, then you're in good shape. If you try to use the JDK's built-in image classes, you'll need all the memory. (Basically, avoid mixing the two types of image manipulation. Immediate mode and deferred mode don't mix well.)
3. All the fancy stuff with ROIs, tiles, and deferred mode are transparent to the program. You just make API call on the JAI class. You only deal with the machinery if you need more control over things like tile sizes, caching, and concurrency.

Answer 2

Here's a suggestion that might be useful;

Try segregating the two main tasks into individual programs. Your first task is to decide which images go where, and that can be a simple mapping from coordinates to filenames, which can be represented as lines of text:

0,0,image123.jpg
0,1,image542.jpg
.....

After that task is done (and it sounds like you have it well handled), then you can have a separate program handle the compilation.

This compilation could be done by appending to an image, but you probably don't want to mess around with file formats yourself. It's better to let your programming environment do it by using a Java Image object of some sort. The biggest one you can fit in memory pixelwise will be 2GB leading to sqrt(2x10^9) maximum height and width. From this number and dividing by the number of images you have for height and width, you will get the overall pixels per subimage allowed., and can paint them into the appropriate places.

Answer 3

Every time you 'append' are you perhaps implicitly creating a new object with one more pixel to replace the old one (ie, a parallel to the classic problem of repeatedly appending to a String instead of using a StringBuilder) ?

If you post the portion of your code that does the storing and appending, someone will probably help you find an efficient way of recoding it.