Differential D29325 Diff 81867 kstars/fitsviewer/fitsdata.h

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kstars/fitsviewer/fitsdata.h

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429 void applyFilter(FITSScale type, uint8_t *targetImage, QVector<double> * min = nullptr, QVector<double> * max = nullptr); 429​ void applyFilter(FITSScale type, uint8_t *targetImage, QVector<double> * min = nullptr, QVector<double> * max = nullptr);
430 430​
431 template <typename T> 431​ template <typename T>
432 void calculateMinMax(); 432​ void calculateMinMax();
433 433​
434 template <typename T> 434​ template <typename T>
435 QPair<T, T> getParitionMinMax(uint32_t start, uint32_t stride); 435​ QPair<T, T> getParitionMinMax(uint32_t start, uint32_t stride);
436 436​
437​ /* Calculate the Gaussian blur matrix and apply it to the image using the convolution filter */
438​ QVector<double> createGaussianKernel(int size, double sigma);
439​ template <typename T>
440​ void convolutionFilter(const QVector<double> &kernel, int kernelSize);
441​ template <typename T>
442​ void gaussianBlur(int kernelSize, double sigma);
443​
437 /* Calculate running average & standard deviation using Welford’s method for computing variance */ 444​ /* Calculate running average & standard deviation using Welford’s method for computing variance */
438 template <typename T> 445​ template <typename T>
439 void runningAverageStdDev(); 446​ void runningAverageStdDev();
440 template <typename T> 447​ template <typename T>
441 QPair<double, double> getSquaredSumAndMean(uint32_t start, uint32_t stride); 448​ QPair<double, double> getSquaredSumAndMean(uint32_t start, uint32_t stride);
442 449​
443 template <typename T> 450​ template <typename T>
444 void convertToQImage(double dataMin, double dataMax, double scale, double zero, QImage &image); 451​ void convertToQImage(double dataMin, double dataMax, double scale, double zero, QImage &image);
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