QA4Camera

Smartphone has been one of the most popular digital devices in the past decades, with more than 300 million smartphones sold every quarter in the world wide. Most of the smartphone vendors, such as Apple, Huawei, Samsung, launch their new flagship smartphones every year. People use smartphone cameras to shoot selfie photos, film scenery or events, and record videos of family and friends. The specifications of smartphone camera and the quality of taken pictures are major criteria for consumer to select and buy smartphones. Many smartphone manufacturers also introduce and advertise their smartphones by introducing the strengths and advantages of their smartphone cameras. However, how to evaluate the quality of smartphone cameras and the taken pictures remains a problem for both smartphone manufacturers and confumers. Currently in the market, there are several teams and companies who evaluate the quality of smartphone cameras and announce the ranking and scores of the quality of smartphone cameras, and the scores of smartphone cameras are subjectively graded by several photographers and experts from different aspects, such as exposure, color, noise and texture. However, subjective assessment is not easy to reproduce, and it is not easy to deploy in practical image processing systems. In the last two decades, objective image quality assessment (IQA) has been widely researched, and a large amount of objective IQA algorithms have been designed to automatically and accurately estimate the quality of images. However, most of objective IQA methods are designed to assess the overall perceived quality of the image degraded by various simulated distortions, which rarely exist in pictures taken by the modern smartphone cameras. Thus these methods are not suitable for the task of smartphone camera quality assessment, while objective evaluation methods specifically designed for the purpose of smartphone camera quality assessment are relatively rare.The purpose of this Grand Challenge is to drive efforts of image quality assessment towards smartphone camera quality assessment. With this Grand challenge, it is expected to develop objective smartphone camera quality assessment models from four different aspects, including exposure, color, noise and texture, by using the datasets released by the organizers. The goal is to provide reference quality rankings or scores for smartphone cameras and to both smartphone manufacturers and consumers.Participants are asked to submit four computational models to cacluate the rankings of smartphone camera from four aspects: exposure, color, noise and texture.

智能手机是近数十年来最具普及性的数字设备之一，全球每季度智能手机销量逾3亿台。包括苹果（Apple）、华为（Huawei）、三星（Samsung）在内的多数智能手机厂商，每年都会推出全新旗舰机型。人们使用智能手机摄像头拍摄自拍照、记录风景或活动，以及录制亲友的日常影像。智能手机摄像头的规格与成像质量，是消费者选购智能手机的核心评判标准之一，诸多厂商也会通过宣传其摄像头的性能优势来推广机型。然而，如何评估智能手机摄像头及其拍摄样张的质量，始终是厂商与消费者共同面临的难题。
当前市场上已有若干团队与企业开展智能手机摄像头质量评估业务，发布摄像头质量的排名与评分；这类评分通常由多位摄影师与专家从曝光、色彩、噪点、纹理等多个维度进行主观打分。但主观评估难以复现，也难以部署至实际的图像处理系统中。
近二十年来，客观图像质量评估（Objective Image Quality Assessment, IQA）领域得到了广泛研究，大量客观IQA算法被提出，用于自动且精准地预估图像质量。但现有多数客观IQA方法旨在评估各类模拟失真图像的整体感知质量，而这类失真在现代智能手机摄像头拍摄的样张中极少出现，因此这些方法并不适用于智能手机摄像头质量评估任务；而专门针对该场景设计的客观评估方法则相对匮乏。
本次大型挑战赛的目标，旨在推动图像质量评估研究向智能手机摄像头质量评估方向发展。依托主办方发布的数据集，本次挑战赛期望从曝光、色彩、噪点、纹理四个维度，构建对应的客观智能手机摄像头质量评估模型。其最终目的是为智能手机厂商与消费者提供可参考的摄像头质量排名与评分。参赛选手需提交四个计算模型，分别从上述四个维度对智能手机摄像头的质量进行排名。

搜集汇总

背景与挑战

背景概述

QA4Camera是一个用于智能手机相机质量评估的数据集，包含1500张图片，来自100个场景和15款智能手机，旨在从曝光、颜色、噪声和纹理四个方面开发客观评估模型。该数据集发布于2019年，属于图像处理领域，适用于推动相机质量评估的算法研究。