تاویل نصوص کی شرعی حیثیت

The two fundamental sources of Islam are the Qur’an and Sunnah (Life) of the Hope Prophet (peace be upon him). Rulings and Legal interpretation are based in light of these two sources, and these two sources are used to determine the correct way of living. Some rulings are clear cut and explicit without any need for interpretation, while other rulings are not so clear cut and are very vague and open to multiple interpretations. Sometimes, in order to understand these vague rulings, there is a need to use different construed methods of interpretations, so that these commandments can become easier to understand and explain. The meaning of construed here is to use those interpretations which is not used commonly in order to explain the verse of life style of the beloved messenger. However, this is not something that any average human being can do, rather one must be a scholar of the highest caliber and have expertise in the field of interpretation. Additionally, the construed interpretation must be valid according to the principles of interpretation, and must have been used before in a previous interpretation. One other thing to note here is that there are many different types of taweel i.e construed interpretations. Some are correct while others are incorrect. This is why it is important to know and understand the correct use of construing and non-construing interpretations in the field of Islamic jurisprudence, so that one can differentiate between the two. Another tragedy of today is that every person thinks that they should and do have the ability to interpret the Qu’ran and the Sunnah on their own, and without any expertise in interpretation, come up with and begin to interpret the Qur’an on their own. This results in wrong interpretations, which not only misguides the individual, but countless others as well. This is a fact that the many different sects in Islam considered deviant by the majority, they all have begun with incorrect and deviant understandings and interpretations on the sacred texts in Islam.

Blind Image Quality Assessment Using Feature Selection Algorithms

The unavailability of reference images in real world problems makes blind image quality assessment (BIQA) a challenging task. The ability of BIQA techniques to assess the image qualityisdirectlydependentonthequalityoffeaturesextracted. ManyBIQAtechniquesare proposed in literature that follow a two-step approach that include extraction of features in different domains and assessment of image quality with the use of extracted BIQA features. TheperformanceofBIQAtechniquescanbedegradedwhenredundantorirrelevantfeatures are present in the image. Therefore, irrelevant and redundant features can be removed using feature selection algorithms that aid in increasing the correlation between predicted quality score and mean observer score (MOS) and lowering the root mean squared error (RMSE), which improves the performance of BIQA techniques. In this thesis, role of feature selection for BIQA has been explored and analyzed. The objectiveoffeatureselectionistoselectfeaturesthatcanhelpinimprovingtheperformance of BIQA techniques. The thesis starts by providing an introduction to image quality assessment followed by a survey of existing state-of-the-art BIQA techniques. The knowledge of existing BIQA techniques is utilized for optimum feature selection, which has not been explored for existing BIQA techniques to the best of our knowledge. In contrast to existing techniques, a three-step framework is presented in this thesis. Existing BIQA techniques are used for feature extraction in the first step. Existing general purpose feature selection algorithms are utilized to reduce the length of feature vector in the second step. The image qualityscoreispredictedutilizingtheselectedfeaturesinthethirdstep. Threeapproachesto feature selection have been considered. Firstly, feature selection is performed using existing feature selection algorithms. During the analysis of features, belonging to various BIQA techniques, it was observed that each distortion type exhibits different characteristics. Each individual distortion type affects each BIQA feature in a distinct manner e.g., Gaussian blur affectsedgeinformationintheimagewhereas,JPEGcompressiondistortiontypeintroduces blockiness in the image. Therefore, using same set of features for all distortion types may not be the optimal approach. Hence, distortion specific feature selection is proposed, which selects different features are selected for each distortion type. Impact of general purpose feature selection algorithms on BIQA techniques has shown promising results. However, thesefeatureselectionalgorithmscanselectirrelevantfeaturesanddiscardrelevantfeatures. Therefore, the performance of fifteen new feature selection algorithms, which are specificallydesignedforBIQA,isexplored. Theproposedfeatureselectionalgorithmsareapplied on the extracted features of existing BIQA techniques and rely on SROCC, LCC, Kendall correlation constant (KCC) and RMSE parameters. Feature selection algorithms based on SROCC and its combination with LCC, KCC and RMSE perform better in comparison to other proposed algorithms. A new BIQA technique based on natural scene statistics properties of the bag-of-features representation and feature selection algorithms is proposed in this thesis. The proposed bag-of-features technique utilizes Harris affine detector and scale invariantfeaturetransformtocomputefeatures, whichareclusteredusingthek-meansclusteringalgorithmtoformthecodebookvocabulary. Thisconstructedcodebookisusedwitha pre-trained support vector regression model to assess the quality of the image. Furthermore, the performance of existing feature selection algorithms is explored on the proposed BIQA technique. Itisobserved,thatfeatureselectionhelpsinimprovingtheperformanceofexistingBIQA techniques,byimprovingtheSROCC,LCC,KCCandRMSEincomparisontousingallthe features for a particular BIQA technique.