Development of depth map from stereo images using sum of absolute differences and edge filters

Abstract

This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.

Quantum drones and the future of military warfare

“…The functions they execute in both commercial and civilian contexts are expected to progressively increase in complexity as time progresses. Here is a compilation of some of their existing capabilities [1], [5], [8], [10], [16], [34], [52]- [54], [59]: -Fully automated flights: Employing traditional techniques can pose difficulties when attempting to chart and monitor extensive regions. Nevertheless, drones equipped with pre-programmed flight routes have the capability to perform this task without the need for manual intervention.…”

“…Due to the ongoing enhancement of their affordability, they are extensively implemented in both the public and private sectors. Autonomous navigation in environments characterized by high intensity of change presents formidable obstacles for drones [34], [46], [52]. Aerospace and defense sectors initially produced drones with counterinsurgency and defense objectives in mind.…”

HFR-Video-Based Stereo Correspondence Using High Synchronous Short-Term Velocities

“…Traditional stereo correspondence algorithms can be categorized into local, global, and semi-global methods. These methods use manually extracted features, such as sum of absolute difference (SAD) [7], normalized cross-correlation (NCC) [8], SIFT (Scale-Invariant Feature Transform) [9], and ORB (Oriented FAST and Rotated Brief) [10], to provide similarity measures between left and right image patches. However, the performance of traditional stereo correspondence methods is severely limited by the handcrafted features used in the cost function.…”