The redundancy in images stems from

Answer: Pixel correlation

• What this means: neighboring pixels often have similar intensities, so knowing one pixel gives information about adjacent pixels. That similarity is called pixel correlation and is the source of redundancy.

• How compression uses it: methods like predictive coding or transform coding (for example, the discrete cosine transform) exploit pixel correlation to represent the image with fewer coefficients or smaller residuals.

• Brief notes on the other choices:

• The phrase "pixel decolleration" is not standard; if interpreted as decreased correlation, that would reduce redundancy rather than explain it.

• Pixel quantization reduces the number of distinct intensity levels (affecting precision and introducing loss), but it is not the primary cause of redundancy.

• Image size changes the total amount of data but does not by itself create redundancy; redundancy is about predictability between pixel values.