High ISO photography has undergone a revolutionary transformation thanks to advances in artificial intelligence denoising technology. Modern photographers can now push their cameras to extreme ISO settings in challenging low-light conditions while maintaining exceptional detail and color quality that was previously impossible to achieve.

A comprehensive comparison conducted by Jason Row Photography puts two leading AI denoising solutions head-to-head: Adobe Lightroom's built-in Denoise feature versus DxO PureRAW utilizing the advanced DeepPRIME 3 technology. The test employed two particularly challenging image files to evaluate real-world performance under demanding conditions.

The first test image was a complex Bangkok night scene captured with a 61-megapixel Sony a7R V camera at an extreme ISO setting of 12,800. The second test file presented an even greater challenge: a 2007 ship photograph taken with a 12-megapixel Nikon D2X at high ISO, representing the kind of older DSLR files that many photographers have archived over the years.

The testing methodology involved processing each raw file through Lightroom's Enhance and Denoise function, then running the same files through PureRAW using DeepPRIME 3 technology. Both processed versions were exported as DNG files and examined at 100% and 200% magnification to evaluate how each application handled critical aspects like shadow noise, color artifacts, and edge preservation.

PureRAW demonstrated superior performance in several key areas, particularly when dealing with noise texture in flat image areas and darker tonal regions. This advantage was especially pronounced when processing the older Nikon D2X file, where PureRAW effectively maintained edge detail while smoothly eliminating harsh luminance noise that can destroy image quality.

While Lightroom often produced results that appeared sharper at first glance, closer examination revealed that this apparent sharpness frequently came from residual noise rather than genuine detail recovery. In contrast, PureRAW's processing of the Bangkok night scene successfully preserved critical details like license plate text and metal surface textures while significantly reducing background noise levels.

The transformation of the older Nikon frame was particularly impressive, converting what was originally a blotchy and rough high-ISO image into something much cleaner and more natural-looking. This improvement not only enhanced the immediate visual appeal but also created a better foundation for subsequent color grading and post-processing work.

From a practical workflow perspective, the comparison revealed important considerations for photographers. PureRAW requires an additional processing step since files must be converted to DNG format before editing can begin in other applications. However, this extra step may be justified by performance gains, as PureRAW processed the large Sony file faster than Lightroom's Denoise function on the same computer system.

The implications for archival photography are particularly significant. The demonstration showed how modern AI denoising software can breathe new life into older image archives, including early DSLR files, travel photography collections, and low-light work from previous years. Photographers can now confidently re-edit legacy images and even consider printing them at larger sizes than previously possible.

The testing approach deliberately kept processing adjustments minimal to isolate the pure effects of denoising technology. This methodology clearly revealed each program's approach to noise reduction, demosaicing, and sharpening without stylistic color grading masking the underlying technical performance. The results provide valuable guidance for photographers determining when to incorporate denoising into their workflow and which solution better matches their editing preferences and technical requirements.