What are the weaknesses of bilevel thresholding?
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Bilevel thresholding has several weaknesses. One common problem is information loss during the image conversion stage, which can result in loss of important details . Another issue is sampling bias caused by spatially inhomogeneous luminous flux, leading to biased thresholding results . Thresholding error is another weakness, as different algorithms can produce different results, introducing processing errors . Resampling errors during three-dimensional reconstruction can also occur, affecting the accuracy of the final result . In terms of specific algorithms, some histogram-based methods may not provide stable performance, while others may not effectively probe the shapes and spatial distribution of the pores in sludge flocs . Overall, these weaknesses highlight the need for careful consideration and optimization of thresholding algorithms in order to minimize processing errors and obtain accurate results.
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77 Citations | The weaknesses of bilevel thresholding include errors in the thresholded output when the object and background gray level populations overlap and when the picture is noisy. |
| The weaknesses of bilevel thresholding are not mentioned in the provided information. | |
| The weaknesses of bilevel thresholding are not mentioned in the provided information. | |
21 Citations | The weaknesses of bilevel thresholding include overestimation of 2D data and poor estimation of the Sierpinski fractal dimension. |
12 Citations | The weaknesses of bilevel thresholding include information loss, sampling bias, thresholding error, and resampling errors. |
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