Farbhistogramme

Farbhistogramme, or color histograms, are a representation of how colors are distributed in a digital image. They quantify the number of pixels that assume each color value, typically by counting occurrences in one or more color channels. For 8‑bit images, each channel usually spans the range 0–255.

Histograms can be computed in different color spaces. A common approach is to build separate one‑dimensional histograms for each channel in a chosen space, such as RGB, HSV, or Lab. Alternatively, a joint three‑dimensional histogram considers combinations of channel values and can capture correlations between channels, at the cost of higher memory usage.

Applications of Farbhistogramme include image enhancement, segmentation, and recognition. Histogram equalization and CLAHE (contrast limited adaptive histogram equalization) use the histogram to improve contrast. Color histograms also support image retrieval and color correction, as they provide a global descriptor of color content and can be used for histogram specification or matching.

Practical considerations involve choosing bin counts and color space. Commonly, 256 bins per channel are used for 8‑bit data, while 32, 64, or 128 bins are also common to reduce memory and computation. In 3D histograms, dimensionality grows quickly. The choice of color space affects robustness to lighting and perception; HSV or Lab spaces are often preferred for perceptual uniformity. Limitations include the loss of spatial information, sensitivity to illumination and white balance, and potential quantization artifacts in the histogram.

Historically, color histograms extend the grayscale histogram concept and have become a standard tool in computer vision and image processing, with broad support in image analysis libraries and applications.