Photo Enlargement

Photo Enhancement Through Image Resizing

Kneson Progressive Photo Enlargement Resampling Engine

The Kneson Progressive photo enlargement method analyzes pixels beyond the immediate pixels of each dot in the image. This photo enlargement method is found in Kneson Software's Imagener Enhanced version. This interpolation method intelligently weighs the difference of colors in outlying pixels far beyond those analyzed by Bicubic analysis. This difference, weighed with the distance to each point or dot in the image, is used to enlarge images with a much more satisfactory result than Bicubic interpolation method produces.

Kneson Progressive++ Photo Enlargement Method

The Kneson Progressive++ photo enlargement method improves on the Kneson Progressive photo enhancement method by leveraging the power of the programming language C++ for pixel information analysis. This method analyzes information for each dot, then performs a second analysis of each pixel in the array of pixels used in the original analysis. This image enlargement method is found in Kneson Software's Imagener Professional version and is more sensitive and complete in its enlargement decision matrix, resulting in sharper edges and more careful blending to image areas containing gradient color changes.

Kneson Unlimited Photo Enlargement Method

The Kneson Unlimited photo enlargement method is the world's first pixel-to-vector enlargement technology, and is found in Kneson Software's Imagener Unlimited version. This enlargement method is a revolutionary departure in enlargement algorithm logic. It does not work with pixels -- it analyzes an image for regions that make up similar color groups at an invisible-to-the-eye detail level. The initial analysis stage creates detailed regions down to the single-pixel level. This enlargement method then analyzes the image complexity, and assigns complexity values to each region, using these values to compute a finely tuned vector array throughout the entire image. The Kneson Unlimited enlargement method then converts these pixel groups into vectors defining regions that make up the content of the image. This process alone vastly improves the look of all images even before enlargement. Once the image has been encoded into regions (vectors), even the most complex images can be resized without limit as the region can be resized like a rubber band. The resulting image has outstanding clarity even at massive proportions.