Image Fusion (Pixel, Feature, Decision Level) — MCQs | Digital Image Processing

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1. Who is responsible for combining raw sensor data in image fusion at the most basic level?



2. Which level of image fusion combines extracted features such as edges or regions from different images?



3. Which level of fusion uses the outputs of classifiers from different sources?



4. Which method generally results in the highest spatial resolution in image fusion?



5. Which fusion level is most appropriate for medical image classification based on multiple imaging modalities?



6. Which of the following is an advantage of pixel-level image fusion?



7. Which is the most computationally intensive image fusion level?



8. What is a primary disadvantage of decision-level fusion?



9. Which technique uses transforms like wavelets in pixel-level image fusion?



10. What is the main advantage of feature-level fusion?



11. In decision-level fusion, which type of model is commonly used?



12. Which of the following is typically used in pixel-level fusion of multispectral images?



13. What does pixel-level fusion directly combine?



14. Which level of fusion is best for applications needing interpretability?



15. Which type of fusion improves classification accuracy by combining predictions from multiple classifiers?



16. In feature-level fusion, what is the typical first step?



17. What type of fusion would be most appropriate when input images have very different resolutions?



18. Which of these techniques is used for dimensionality reduction in feature-level fusion?



19. Which image fusion level is considered least sensitive to misregistration errors?



20. Which of the following methods can be applied for pixel-level fusion in thermal and visible image fusion?



21. What is the key benefit of decision-level fusion in surveillance applications?



22. Which level of fusion is most affected by noise and misalignment?



23. Which method is commonly used to align images before pixel-level fusion?



24. Which fusion level best supports integration of heterogeneous data types?



25. What type of learning model can be used for feature-level fusion?



26. Which of the following describes a major challenge in feature-level fusion?



27. What is the output of pixel-level image fusion?



28. Which level of fusion would be best for combining RGB and thermal images for object detection?



29. Which one is not a benefit of image fusion?



30. Which technique is not typically involved in pixel-level fusion?



31. What is required before performing pixel-level fusion on multiple images?



32. Which method is useful for reducing redundancy in feature-level fusion?



33. Which decision-level fusion technique combines results based on probability distributions?



34. Which technique is often used to evaluate the effectiveness of image fusion?



35. In which application is decision-level fusion commonly used?



36. Which of the following uses raw pixel intensities from multiple sensors?



37. Which is a common tool for feature extraction before fusion?



38. Which metric is used to assess quality of fused images?



39. Which fusion method is best suited for compressing complementary features from different sensors?



40. Which of the following improves classification by combining multiple predictions?



41. Which of the following fusion levels can be used without needing spatial alignment?



42. Which feature-level fusion technique transforms images into uncorrelated components?



43. Which level of fusion is typically used when raw image quality is poor but high-level decisions are possible?



44. What is a common problem in pixel-level fusion?



45. Which fusion technique is likely to be used in autonomous vehicles?



46. Which method is likely to be used in real-time applications requiring speed over precision?



47. Which feature extraction method is best suited for texture-based fusion?



48. Which sensor fusion level is often used in biometric systems like face and fingerprint fusion?



49. Which fusion strategy uses different combinations of fusion levels?



50. Which fusion level requires the least data storage?



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