Abstract: An approach is provided for color clustering for preprocessing an image. A cross-product on values of pixels in a source image and a number of bits per channel is determined, rounded to integer values, and left aligned to specify a target image. The following actions are repeatedly performed until a count of colors in the target image equals a target: a least frequent color in the target image is identified, distances between the least frequent color and other colors in the target image are determined, a least distance among the distances is determined, where the least distance is between the least frequent color and a closest color, a merged color is generated by merging the least frequent color and the closest color, and the count of the colors in the target image is reduced by replacing the least frequent color and the closest color with the merged color.

Abstract: An approach is provided for color clustering for preprocessing an image. A cross-product on values of pixels in a source image and a number of bits per channel is determined, rounded to integer values, and left aligned to specify a target image. The following actions are repeatedly performed until a count of colors in the target image equals a target: a least frequent color in the target image is identified, distances between the least frequent color and other colors in the target image are determined, a least distance among the distances is determined, where the least distance is between the least frequent color and a closest color, a merged color is generated by merging the least frequent color and the closest color, and the count of the colors in the target image is reduced by replacing the least frequent color and the closest color with the merged color.

Abstract: In an approach to image compression while retaining feature information at original coordinates, one or more computer processors compress an image while retaining pattern and feature information at original coordinates, wherein the image is a full resolution 3D image. The one or more computer processors create one or more image subsets based on the one or more determined regions of interest identified by utilizing a first pass selection of the regions of interest based on the compressed image. The one or more computer processors train one or more models based the created one or more image subsets that contain one or more regions of interest based on the compressed image.

Abstract: In an approach to image compression while retaining feature information at original coordinates, one or more computer processors compress an image while retaining pattern and feature information at original coordinates, wherein the image is a full resolution 3D image. The one or more computer processors create one or more image subsets based on the one or more determined regions of interest identified by utilizing a first pass selection of the regions of interest based on the compressed image. The one or more computer processors train one or more models based the created one or more image subsets that contain one or more regions of interest based on the compressed image.