(H2, all C, S5, O2)
Implement the histogram calculation algorithm. The application should be able to save the histogram of the chosen channel as an image (--histogram). Next, implement the given method of image quality improvement basing on image histogram and calculate all the image characteristics. It should be analyzed what is the influence of quality improvement methods on those characteristics for different sample images. The available variants are:
[x] (H2) Exponential final probability density function (--hexponent). @rostekus
Image characteristics (each team should implement all of them):
[x] (C1) Mean (--cmean). Variance (--cvariance).
[x] (C2) Standard deviation (--cstdev). Variation coefficient I (--cvarcoi).
[x] (C3) Asymmetry coefficient (--casyco).
[x] (C4) Flattening coefficient (--casyco).
[x] (C5) Variation coefficient II (--cvarcoii).
[x] (C6) Information source entropy (--centropy).
Implement linear image filtration algorithm in spatial domain basing on convolution. This algorithm should be implemented twice. First implementation should be universal and should work for each mask. Second implementation should be optimized for a chosen mask. The optimization should consider reduction of operations number and memory needed for image filtration. The available variants are:
[x] (S5) Extraction of deteials III. Without direcition, laplacian filter (--slaplace). @rostekus
Implement non-linear image filtration algorithm in spatial domain. It should be analyzed what is the result of the filtration for different sample images. The available variants are:
[x] (O2) Roberts operator (--orobertsii). @eryk-poradecki
rostekus
commented
10 months ago
(H2, all C, S5, O2) Implement the histogram calculation algorithm. The application should be able to save the histogram of the chosen channel as an image (--histogram). Next, implement the given method of image quality improvement basing on image histogram and calculate all the image characteristics. It should be analyzed what is the influence of quality improvement methods on those characteristics for different sample images. The available variants are:
Image characteristics (each team should implement all of them):
Implement linear image filtration algorithm in spatial domain basing on convolution. This algorithm should be implemented twice. First implementation should be universal and should work for each mask. Second implementation should be optimized for a chosen mask. The optimization should consider reduction of operations number and memory needed for image filtration. The available variants are:
Implement non-linear image filtration algorithm in spatial domain. It should be analyzed what is the result of the filtration for different sample images. The available variants are: