Dfine for Mac
Dfine is a well organized Mac application designed to help you reduce the noise level from your images without making you deal with complex tools. The app is able to measure the noise level and create custom profiles, and allows you to make adjustments by using control points or by modifying the color ranges.
Powerful noise reduction utility that is included in the Nik Collection by Google
The Dfine app is part of the Google Nik Collection, which means that it is not available as a separate software solution: you must download, install, and purchase the entire tools collection. Besides the image processing applications, the Nik Collection package also includes user friendly installation and uninstallation utilities.
To get started, navigate to the Nik Collection folder placed in the Applications directory, and launch the Dfine app. The next step is to import the images you want to process by dragging and dropping them on top of the Dfine Dock icon.
Intuitive adjustments tools designed to help you modify the image noise
The Dfine user interface is represented by a large window where you can preview both the source image and the output result. All the adjustment tools are placed in a well organized panel located on the right side of the main window.
Right off the bat, you get to measure the noise level and Dfine will automatically generate a profile that will modify only the noise elements: this way, the final result will retain more of the original content. However, you can also apply filters manually, by creating multiple control points.
Uncomplicated yet very efficient noise reduction solution
Dfine provides extensive control over your own images without making you deal with complicated tools and settings: most of the adjustments are performed via intuitive slider bars.
Moreover, the app enables you to preview the results in real time, side by side, or in a loupe window: this way you can judge for yourself if the output still needs work, or can be saved to the disk (note the app is replacing the original images).