## 1 Introduction  
Optical microscopic imaging is a versatile and widespread tool in modern life science, fundamental physics, and chemistry. Exploring and breaking the optical imaging limitations, e.g., resolution and contrast, is the primary task. Exploiting the quantum properties of light is one way to overcome some of those limitations. Ghost imaging is one of the subfields of quantum imaging that exploits quantum or spatial intensity-fluctuation correlations to image objects with resolution, contrast, or other imaging criteria that can go beyond classical optics [1; 2; 3]. Ghost imaging can nonlocally image an object using photons that have not interacted with the object [4]. Theories and experiments have shown that both entangled photon interference and classical intensity-fluctuation correlations could be used for ghost imaging. In 1995, the first successful ghost imaging experiment relied on entangled photon pairs generated by spontaneous parametric downconversion [5]. This experiment was the first use of light containing spatial quantum correlations to illuminate an object to be imaged in quantum imaging. Soon afterward, [PERSON] et al. [6] presented an experimental demonstration of ghost imaging by using a pseudothermal light source. Strictly speaking, pseudothermal ghost imaging is no longer quantum imaging in the full sense, even if there are partial quantum correlations that exist in pseudothermal light. It is well known that the image quality of quantum ghost images is much better than in pseudothermal ghost imaging, but it is limited by wavelength [7; 8; 9]. Pseudothermal ghost imaging is very flexible regarding wavelength, e.g., X-ray ghost imaging [10; 11; 12]; thus, this technology has attracted more attention. In recent years, ghost imaging with pseudothermal light sources has been investigated extensively [13; 14; 15; 16] to overcome the limitations of image quality, which depends on detection contrast. Many strategies significantly improve the image quality in pseudothermal ghost imaging. One approach realizes a high-quality image by using high-order correlation [17; 18; 19; 20]. However, it is hard to reach the theoretical limit of the contrast in high-order ghost imaging. The other important approach is implementing speckle-based imaging methods [21; 22; 23; 24]. Recent results [25] have demonstrated the scaling laws for the achievable contrast of the retrieved ghost images, which strongly depend on the ratio between object size and the speckle size of the pseudothermal light for the same number of independent iterations. There are also various approaches focused on improving the imaging quality by using computational methods, e.g., sparsity constraints [26; 27], THz patterns [28; 29], differential ghost imaging [30], and computational ghost imaging by using special patterns [31; 32; 33; 34; 35]. Based on these studies, the improvement of pseudothermal ghost imaging quality has been greatly promoted. The listed studies generally concern the ghost imaging algorithm and the influence of special speckle patterns on ghost image quality. In microscale pseudothermal ghost imaging, the diffused light is weak and easily disturbed by stray light in detection. Thus, in addition to speckle patterns and size, the influence of the histopathologic pixel intensity distribution of the speckle fields must be considered; i.e., we have to evaluate the probability distribution of the normalized signal levels measured on a single pixel of our camera. To our knowledge, classical ghost imaging with different pixel intensity distributions of the speckle fields from a nonuniform pseudothermal light source has not been discussed yet. In this paper, we report on the influence of the speckles' pixel intensity distribution from the nonuniform pseudothermal light source on the measured contrast-to-noise ratio (CNR) in microscale ghost imaging.