This study explores the impact of six fundamental visual features—hue, lightness, saturation, contrast, clarity, and color complexity—on the emotional evaluation of images in terms of valence and arousal, using a digitalized affective picture system. Two sub-studies were conducted: Study 1 analyzed the differences in emotional evaluations among image sets with identical content but varying visual features, while Study 2 examined how changes in individual visual features influence emotional perception under controlled conditions. The results show that, although specific visual features significantly affect emotional evaluations with varying degrees of impact, the overall process of image-based emotion evaluation remains systemic, with interactions between visual features jointly shaping emotional responses. This research clarifies the underlying relationship between visual features and emotion perception, providing new empirical support and practical implications for advancing affective computing and image-based emotional assessment systems.