Display of stereo images is widely used to enhance the viewing experience of three-dimensional imaging and
communication systems. In this paper, we propose a method for estimating the quality of stereoscopic images
using segmented image features and disparity. This method is inspired by the human visual system. We believe
the perceived distortion and disparity of any stereoscopic display is strongly dependent on local features, such
as edge (non-plane) and non-edge (plane) areas. Therefore, a no-reference perceptual quality assessment is
developed for JPEG coded stereoscopic images based on segmented local features of artifacts and disparity.
Local feature information such as edge and non-edge area based relative disparity estimation, as well as the
blockiness and the blur within the block of images are evaluated in this method. Two subjective stereo image
databases are used to evaluate the performance of our method. The subjective experiments results indicate our
model has sufficient prediction performance.
This research aims to develop an objective no-reference video quality evaluation method for MPEG-2 MP@ML
coded (symmetric and asymmetric) stereoscopic videos. Our proposed method is based on segmented local
features of spatial artifacts, disparity, and temporal activities of videos. Segmented local features information
such as edge and non-edge areas of any stereoscopic pair frames (i.e., left and right views) have taken into
consideration for blockiness and zero crossing. In this method, a temporal segmentation approach is considered
and each temporal segment is evaluated for artifacts and disparity. Temporal features are calculated separately for
left and right video sequences based on segmented local features and sub temporal segment. Different weighting
factors are also applied to measure the spatial artifacts, disparity, and temporal features of the segment. In
order to verify the performance, we conducted subjective experiment on different symmetric and asymmetric
coded (Bit rates: 2, 3, 5, and 8 Mbps) stereo video pairs. An auto stereoscopic display was used for fifteen
(15) reference stereo videos; each of the video was 15 seconds length and the total length of each test sequence
was (15×15 sec = 3 min 45 sec). Seven video sequences were used to complete the experiment. The Single
Stimulus Continuous Quality Evaluation (SSCQE) method was used to conduct our subjective experiment. The
experiment result indicates that our proposed method has given sufficient prediction performance.
The importance of the perceived quality measurement is fundamental for many image processing applications, such as compression, acquisition, restoration, enhancement, and reproduction. Color information is also of great importance for the perceived image quality, although perceived information is mainly represented by luminance. We present a computational and memory-efficient no-reference image quality assessment model independent of JPEG and JPEG2000 coded color images based on local regions. We also present the discrimination algorithm for these two types of coded images. The features of local regions are blockiness around the block boundary, average absolute difference between adjacent pixels within the block, and zero crossing rate within the block of the image. We validate the performance of our model on our subjective database, which shows good quality prediction performance, and the model's generalization ability is also verified on the other database.