What is one significant change that can be achieved by applying smoothing to images?

Applying smoothing to images is primarily aimed at reducing sharp edges and noise, which is why this option is the most significant change associated with this process. Smoothing techniques, such as Gaussian blurring, effectively lessen the abrupt variations in pixel intensity found in images, which manifest as noise or sharp lines. By averaging the pixel values of neighboring pixels, the resulting image appears more uniform and less cluttered, allowing for easier interpretation and analysis.

The other options, while they might describe processes or outcomes in image processing, do not align with the primary goal of smoothing. For example, introducing new colors typically involves other techniques such as color manipulation or adjustment, rather than smoothing. Increasing overall contrast often requires contrasting enhancement techniques, which are counter to the intent of smoothing. The combination of multiple images pertains to image registration or fusion strategies, which is separate from the smoothing process altogether.