The phrase "aspect of the image" is correct and usable in written English.
It can be used when discussing specific features, qualities, or elements that make up an image or visual representation.
Example: "The aspect of the image that caught my attention was the vibrant color palette used throughout the composition."
Alternatives: "feature of the image" or "element of the image".
She arranges her models, using her hands to feel every aspect of the image, instructing her assistant where to place the edges of the frame.
Indeed, the cats are not the only stealthy aspect of the image: subtle dissonances abound, giving it that tension between celebration and critique that is a trademark of Mr. Owens's best work.
The 3D aspect of the image is achieved by measuring the time it to takes for the photon from the laser pulse to be reflected back, which in turn allows the camera to determine depth.
The colourised scale on the right aspect of the image is in mgI/ml.
Several extractors can be implemented in a CBIR system, and each of them refers to one aspect of the image.
A VERTIPH design incorporates three different views, each tailored to a different aspect of the image processing system under development; an overall architectural view, a computational view, and a resource and scheduling view.
The realistic aspect of the images sets down the physical lay of the land, as it were, trapped in a present of calcified political stances, with the common people caught between them.
Yet there's still another aspect of the images that puts the movie squarely in the front lines of the artistic times: these great images seem to have a heavy black frame around them, something like visual quotation marks, which make them seem to have been derived from other romantic melodramas rather than created afresh for this movie.
However, as expected given the degraded aspect of the images, the performance was lower than she had achieved previously with non-equalized images (79.3%, χ2 = 125.35, df = 1, P<0.0001).
Note here that the degraded aspect of the images is such that the performance with new images is below usual acquisition criteria for discrimination learning (for instance 75% correct in [12]) but mean accuracy on new images was above chance and comparable (if not better) than human subjects.
