When two regions in an image (like background and object) have overlapping pixel intensities, choosing a single threshold T becomes tricky:
If T is too low, background pixels might be wrongly classified as object (false positives).
If T is too high, object pixels might be lost (false negatives).
So, in overlapping cases, a bad choice of T can drastically reduce segmentation accuracy. You may need more advanced methods (like adaptive thresholding or clustering) instead of global thresholding.
Also regarding gamma correction
Gamma correction with
𝛾<1 brightens the image even more.
For an image that’s already bright, applying
γ<1 can lead to:
Washed-out appearance (loss of contrast in highlights)
Loss of detail in bright areas, as many pixels might shift toward the max intensity (255)
So, it's usually not ideal to apply γ<1 to bright images — unless you’re aiming for a specific visual effect.