An underwater-imaging-model-inspired no-reference quality metric for images in multi-colored environments

In multimedia transmission, it is important to rely on an objective quality metric which accurately represents the subjective quality of processed images and video sequences. Reduced-reference metrics make use of side-information that is transmitted to the receiver for estimating the quality of the received sequence with low complexity. In this paper, an Edge-based Dissimilarity Reduced-Reference video quality metric with low overhead bitrate is proposed. The metric is evaluated by finding the dissimilarity between the edge information of original and distorted sequences. The edge degradation can be detected in this manner as perceived video quality is highly associated with edge structural. Due to the high overhead using the Soergel distance, it is pertinent to find a way to reduce the overhead while maintaining the edge information that can convey the quality measure of the sequences. The effects of different edge detection operator, video resolution and file compressor are investigated. The aim of this paper is to significantly reduce the bitrate required in order to transmit the side information overhead as the reduced reference video quality metric. From the results obtained, the side information extracted using Sobel edge detector maintained consistency throughout the reduction of spatial and temporal down-sample.

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No-reference quality metric for contrast-distorted image based on gradient domain and HSV space

Journal of Visual Communication and Image Representation ◽

10.1016/j.jvcir.2020.102797 ◽

2020 ◽

Vol 69 ◽

pp. 102797 ◽

Cited By ~ 1

Author(s):

Wenjing Lyu ◽

Wei Lu ◽

Ming Ma

Keyword(s):

Quality Metric ◽

Distorted Image ◽

Gradient Domain ◽

Reference Quality

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Accurate binocular stereo underwater measurement method

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419864468 ◽

2019 ◽

Vol 16 (5) ◽

pp. 172988141986446

Author(s):

Xiaojun Wu ◽

XingCan Tang

Keyword(s):

Measurement Accuracy ◽

Calibration Method ◽

Correction Method ◽

Image Correction ◽

Underwater Imaging ◽

Epipolar Constraint ◽

Imaging Model ◽

Internal Parameters ◽

Extrinsic Parameters ◽

Binocular Stereo

Light changes its direction of propagation before entering a camera enclosed in a waterproof housing owing to refraction, which means that perspective imaging models in the air cannot be directly used underwater. In this article, we propose an accurate binocular stereo measurement system in an underwater environment. First, based on the physical underwater imaging model without approximation and Tsai’s calibration method, the proposed system is calibrated to acquire the extrinsic parameters, as the internal parameters can be pre-calibrated in air. Then, based on the calibrated camera parameters, an image correction method is proposed to convert the underwater images to air images. Thus, the epipolar constraint can be used to search the matching point directly. The experimental results show that the proposed method in this article can effectively eliminate the effect of refraction in the binocular vision and the measurement accuracy can be compared with the measurement result in air.

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