quscope.image_processing.quantum_segmentation

Quantum image segmentation using Grover’s algorithm and amplitude amplification.

This module provides quantum algorithms for image segmentation tasks, including threshold-based, edge-based, and region-based segmentation. It implements Grover’s algorithm with custom oracles for different segmentation criteria and provides utilities for result interpretation and visualization.

Functions

apply_grovers_algorithm(circuit, oracle[, ...])	Apply Grover's algorithm for image segmentation.
calculate_optimal_iterations(marked_items, ...)	Calculate the optimal number of Grover iterations.
create_custom_oracle(circuit, oracle_function)	Create a custom oracle using a user-defined function.
create_edge_oracle(circuit, image_shape[, ...])	Create an oracle for edge-based segmentation.
create_pattern_oracle(circuit, target_pattern)	Create an oracle that marks specific target patterns.
create_region_oracle(circuit, seed_points, ...)	Create an oracle for region-based segmentation.
create_threshold_oracle(circuit, threshold)	Create an oracle for threshold-based segmentation.
interpret_results(result_counts, image_shape)	Interpret the results of quantum image segmentation.
optimize_circuit(circuit)	Optimize a quantum circuit for better performance.
segment_image(img_array[, method, ...])	Segment an image using quantum algorithms.

Classes

SegmentationMethod(value[, names, module, ...])	Enumeration of supported segmentation methods.
SegmentationResult(counts, original_shape, ...)	Class to store and analyze segmentation results.

Exceptions

OracleConstructionError	Exception raised when oracle construction fails.
SegmentationError	Base exception for segmentation errors.