Developer motto


Raw Image Analyser Screenshots

Compare mode with image difference


The application's main goal is to allow dynamic and informative Side-By-Side image
comparison with emphasize on RAW images and flexible means to adopt varying loading of
input files.

The S-B-S image comparison is the core feature which allows a user to analyze image
pixels of N correlated images in the most effective way. This is achieved by selecting
several images (refer to Hot-Keys and Mouse control section) and then every action taken
on one of them is affecting the entire group (comparison party).
Note that the application takes the approach of minimal layout overhead i.e. there's no
usage of tool-bars, over rich menus or pop-up windows. This is done to enable the maximal
focus on image's data / pixels. All actions can be quickly accessed via a compact set of
hot-keys and minimal mouse actions.

It's also possible to work with the software via command line and configuration file.
At the bottom you'll find an informative Status-bar that holds file info, image info and
app modes info.

One of the problems with RAW images, such that simply pack a group of pixels, is that
they carry no meta info such that a SW might parse and be able to open them with a single
click. As such, the app offers a "pseudo-training" feature that uses a powerful tool
called reg-ex (short for regular expression). If you're a developer, then this is a must
know for but if you're not, know that 99% of all daily-used patterns can be matched with
such a reg-ex string pattern matching. All is required from you is to direct the app (see
Formats file section) how to parse a file name with a variety of group options.

Although the app flag-feature is RAW images (mainly luma, RGB and YUV family), you can
still use it to open most common file types like JPG, PNG, BMP, TIFF and others.
The app is used mainly for viewing and thus, it refrains from "touching" the input
images unless the user specifically directs a file save over them.

Histogram view in compare mode


The histogram view shows an image statistical info with an emphasize on histogram datum.
It's key-feature is allowing user browsing of the histogram bins and reflecting a
per-channel info.

When the overlay is on, all regular user-actions are in order and the info will be
updated accordingly.

This is specially useful when working with ROI as the current view always reflects the
current active ROI, whereas non-active ROI simply displays info for the entire image.
Note that when an image is filtered, only the unmasked pixels (visible) are part of the
statistics / histogram view datum.

Image Evaluating using I-Eval


To enhance your analyzing process, you can use the I-Eval engine to produce most
possible image manipulations. 
In this example, we used these 2 I-Eval expressions:

{ abs(i-i[x-1,y-1]]) } { i1*1.3*(i2 > 10)+i1/4*(i2 <= 10) } 

This yields diagonal XY gradient on image 2 which is piped to the 2nd I-Eval that simply 
enhances the pixels that have gradient bigger than 10 and dims those that aren't by a factor 
of 4.
You can use this later to compare or further manipulate your images...

Filtered image


Example of converting an image into gray scale and filtering (masking) part of the luma values (lower half).

You can see the grid mode is aware of the actual filtered colors, making it easier to distinguish the area.