ITK OtsuMultipleThresholdsImageFilter无输出问题求助

Hey there, let’s work through this frustrating problem with ITK’s OtsuMultipleThresholdsImageFilter! It’s great that you’ve got the OpenCV-to-ITK bridge working and can visualize the image with QuickView—so the data itself is solid. The empty thresholds usually boil down to a few common oversights with ITK’s filter execution model. Let’s break down the fixes:

Common Causes & Fixes #

1. You Forgot to Trigger Filter Execution with Update() #

ITK uses a lazy execution model—filters don’t run calculations until explicitly told to. QuickView might be calling Update() under the hood when rendering the image, but when you’re using the filter directly, you have to trigger it manually.

If your code skips filter->Update() before calling GetThresholds(), the filter hasn’t actually computed anything yet, hence the empty result. Always add this step (and wrap it in a try-catch to catch errors):

try {
    otsuFilter->Update();
} catch (const itk::ExceptionObject& err) {
    std::cerr << "Filter execution failed: " << err << std::endl;
    // Handle error here
}

2. You Didn’t Set the Number of Thresholds #

The OtsuMultipleThresholdsImageFilter needs to know how many thresholds you want to compute. If you skip calling SetNumberOfThresholds(), it defaults to 0—so no thresholds are generated. Make sure you set this to a valid number (e.g., 2 for 3 regions):

otsuFilter->SetNumberOfThresholds(2); // Adjust based on your use case

3. Mismatched Image/Filter Template Parameters #

Double-check that your filter’s template matches your input image’s pixel type and dimension. For example, if your ITK image is a 2D unsigned char image, your filter should be instantiated like this:

using ImageType = itk::Image<unsigned char, 2>;
using FilterType = itk::OtsuMultipleThresholdsImageFilter<ImageType, ImageType>;

Using incompatible types (like float pixels when the filter expects integer types) can silently fail or produce no thresholds.

4. Verify Image Properties #

Even if QuickView shows the image, double-check that it has valid metadata:

• Ensure the image isn’t empty (inputImage->GetLargestPossibleRegion().GetNumberOfPixels() > 0)
• Confirm the pixel range makes sense (e.g., 0-255 for 8-bit images)

Full Working Example Snippet #

Putting it all together, here’s a corrected workflow for your use case:

// Assume ImageType is correctly defined, and inputImage is your converted ITK image
using FilterType = itk::OtsuMultipleThresholdsImageFilter<ImageType, ImageType>;
FilterType::Pointer otsuFilter = FilterType::New();

// Configure the filter
otsuFilter->SetInput(inputImage);
otsuFilter->SetNumberOfThresholds(2); // Set your desired threshold count
otsuFilter->SetLabelOffset(1); // Optional: Adjust output label starting value

// Execute the filter
try {
    otsuFilter->Update();
} catch (const itk::ExceptionObject& err) {
    std::cerr << "Error: " << err << std::endl;
    return;
}

// Retrieve thresholds
const auto& thresholds = otsuFilter->GetThresholds();
if (thresholds.empty()) {
    std::cerr << "No thresholds returned—check filter configuration!" << std::endl;
} else {
    std::cout << "Computed thresholds: ";
    for (const auto thresh : thresholds) {
        std::cout << thresh << " ";
    }
    std::cout << std::endl;
}

If you still run into issues after trying these steps, enabling ITK’s debug output might help pinpoint the problem—add otsuFilter->DebugOn(); before updating to get more detailed logs.

内容的提问来源于stack exchange，提问作者John_Sharp1318