Final answer:
Global image features by Oliva and Torralba include the degree of naturalness, openness, roughness, expansion, and color, which are used in image interpretation in computer vision.
Step-by-step explanation:
The question refers to global image features proposed by Oliva and Torralba which include a degree of naturalness, degree of openness, degree of roughness, degree of expansion, and color. These features are used to analyze and interpret images, particularly in the field of computer vision and image processing.
Naturalness relates to how natural an image appears, which can involve factors like colors (green, blue, red) and diversity of land-uses. Openness refers to how open or enclosed a space feels within an image, while roughness measures the perceived texture quality in an image, such as rough, pebbly, or smooth surfaces. Expansion indicates the perceived depth and dimensions (height, width, length) of the space shown in the image. Lastly, color is an essential feature that contributes to the emotional and compositional qualities of an image, influencing contrast (light vs. dark), depth perception (near vs. far), and the overall aesthetic appeal